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Paper Citation Record · LEDGER

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops

As of 15 August 2026, this Paper Citation Record lists 100 of 205 outbound references and 3 inbound Pith citation observations for arXiv:2607.07663.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.07663 v1

Coverage vector

measured 100 of 205 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T03:36:57.168246Z

measured 103 of 103 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:20:58.764730Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-08T19:13:05.876662Z

Reference resolution

100 of 205 outbound references displayed

  • verified exact81
  • verified fuzzy13
  • unresolved0
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 924a1b74-03e4-497d-a8e6-02987c586574 · outbound

This paper cites Advances in Computers , year = 1966, volume =.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Advances in Computers , year = 1966, volume =

Reference 1

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metadata mismatch
doi, observed 2026-07-09T03:45:55.294957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:57cec40d557cafdbdfcb28330a85beef05e7ba988f7d36358b0b2a6f747776d7

Observation a3306a95-bd9d-4753-a83b-12bd56b5f12f · outbound

This paper cites Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements

Reference 2

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.707246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6b018869-fe93-4ecf-99e0-04d360676e93 · outbound

This paper cites Gupta, Neereja Sundaresan, Thomas Alexander, Christopher J.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Gupta, Neereja Sundaresan, Thomas Alexander, Christopher J

Reference 3

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doi_truncated, observed 2026-07-09T03:45:55.306458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:d4376d87089216ff2e546ebcaed23f4ea45c6cf4b0a1308e592da127cc607ebe

Observation 42a28d46-4fdb-4dc0-a0d0-4998af53f8f6 · outbound

This paper cites AlphaEvolve: A coding agent for scientific and algorithmic discovery.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops AlphaEvolve: A coding agent for scientific and algorithmic discovery

Reference 4

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.689363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0424696d6fe25d2a49c089439414744bb774f220b4677ba2213dbce9948524da

Observation 827118e0-7111-4c47-8aae-65213ee727f8 · outbound

This paper cites Recursive self-improvement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Recursive self-improvement

Reference 5

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verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.854506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:fd0fb5fd0291e56700d3bfaa10ea59e99f36e4736a19fa72114ddf1a7dba730c

Observation 1dc23bea-2261-4051-aec6-d66c3c7a4ca8 · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Self-Refine: Iterative Refinement with Self-Feedback

Reference 6

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.694490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:350c0f2e4be0e9917946897be38570657cd6b04efc9025fe8f064dc61026e0b4

Observation a9c5853f-9068-42f0-8b00-fb7ae44110c8 · outbound

This paper cites STaR: Bootstrapping Reasoning With Reasoning.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops STaR: Bootstrapping Reasoning With Reasoning

Reference 7

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.603171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:eda86a0052e4f236073b4e475735fc6fd9c5ca40db7b6b6c3696f26450db56da

Observation 47f64fd4-1aa6-4d0e-89f7-1d4fef9652ac · outbound

This paper cites Self-Rewarding Language Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Self-Rewarding Language Models

Reference 8

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.566585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:fe6e0b33e65a0f9f8d0c1669643f55d8fcd574ec8fd42541bad6aa3c24382136

Observation 2670b99e-e1a7-4828-b27a-05acc4bd3850 · outbound

This paper cites G\"odel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops G\"odel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement

Reference 9

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.686930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:454dd30e3f5ea38b608c7b7810607371a342938b689b2c0d2bfd49fbfa013ad4

Observation 27c9302d-3ffb-4dd7-987e-2807dd4b54e7 · outbound

This paper cites Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents

Reference 10

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local_arxiv, observed 2026-07-09T03:45:55.491699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:365dbcaaaf9615fc3e54c87ba39a3c7d78b37725828ed3538d58d21cf16e75c1

Observation bbbf90fa-8e25-4321-aa3f-c7acb26e9583 · outbound

This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 11

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local_arxiv, observed 2026-07-09T03:45:55.494637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:98cb2c4449374a1f3b0b14ef82528eafab22574414cf6f6bb619953aa02864c5

Observation 052e9a6c-63a9-4580-b7fd-d91ba08b696b · outbound

This paper cites A survey of on-policy distillation for large language models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops A survey of on-policy distillation for large language models

Reference 12

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verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.851012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:2ec6d89e16a1cd3ee8985490c902bae4e0468ade24ef6dd4bcd7b8efc39583d9

Observation bbef61b5-a851-4405-a3a4-b657e4e3abf6 · outbound

This paper cites A Survey of On-Policy Distillation for Large Language Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops A Survey of On-Policy Distillation for Large Language Models

Reference 13

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.441411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:ce3febab6d9cdf578633761178aafa24c12c7d9e64bf349c9cbac8294e65ae54

Observation a1a3d738-edce-4b76-b7a8-799c8afd63b7 · outbound

This paper cites arXiv preprint arXiv:2510.09988 , year=.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops arXiv preprint arXiv:2510.09988 , year=

Reference 14

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arxiv_id, observed 2026-07-09T03:45:55.334811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:6a4afa9a736e558f61a3fe63700d7b59dd19f592bdd065eceff036cf128e7c94

Observation d10a4a27-4f14-47f5-b805-1ea73dee3e74 · outbound

This paper cites Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting

Reference 15

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.682090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:1d8150a1be493a314264ae2b83ed0d3a63629bfdba9bfed62cfc5f5c7aa3bd3f

Observation e43774be-18a1-4117-a0e2-0863382af65f · outbound

This paper cites Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Absolute Zero: Reinforced Self-play Reasoning with Zero Data

Reference 16

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.486406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:4acd5fd16059820897b1f06d77ea6e41bea8d834fa0197b23c1e40d3f4aad06b

Observation 857b53ab-0e68-4f7c-ba70-2d66271365a5 · outbound

This paper cites R-zero: Self-evolving reasoning LLM from zero data,.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops R-zero: Self-evolving reasoning LLM from zero data,

Reference 17

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verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.852954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:646fcabccd15e429d6abe2bae15f8e0c397f39dbe6b6fe328a286d99b22045e9

Observation d1e883d4-5917-4f10-98a4-694c69c58a7f · outbound

This paper cites R-Zero: Self-Evolving Reasoning LLM from Zero Data.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops R-Zero: Self-Evolving Reasoning LLM from Zero Data

Reference 18

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.692092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:b85222eb678e93575e8343a77eccc7581df8e3ef7c599b14f815d37083f76414

Observation 352bb85d-3d45-4c2f-b8b7-c7da9965ade6 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Reflexion: Language agents with verbal reinforcement learning

Reference 19

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verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.856495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:077cc7013a74ab50f09872c3542e2e162f32c2be11f4320a5cb8eabfd6275f6b

Observation 7610a1d6-3d30-441d-b690-e5127226deb5 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 20

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.798979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:dbf32b38b06d024090da6b8005f24c581a9158797ee83cef69e9e671d195129e

Observation 29d75de8-38d5-4b8e-bdc1-eaeb5823c2c9 · outbound

This paper cites SymbolicAI: A framework for logic-based approaches combining generative models and solvers.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SymbolicAI: A framework for logic-based approaches combining generative models and solvers

Reference 21

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local_arxiv, observed 2026-07-09T03:45:55.478269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:79f9c39208f4860c1cb1d65599071ae12710a10678f4815b63c7f3db52955b43

Observation f628b8f8-0c10-452e-a5fb-bb8a7d74ec68 · outbound

This paper cites Towards Reliable and Robust LLM Planning: Symbolic Feedback-Driven Iterative Self-Refinement Framework.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Towards Reliable and Robust LLM Planning: Symbolic Feedback-Driven Iterative Self-Refinement Framework

Reference 22

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.666272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:ca2b3d8569d4c4b6fec7c468f77a271c0dc11f43fa86736fefbf3f6cfd18f237

Observation be853cc6-f306-4a83-8a2d-346b681b8555 · outbound

This paper cites SQL-o1: A Self-Reward Heuristic Dynamic Search Method for Text-to-SQL.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SQL-o1: A Self-Reward Heuristic Dynamic Search Method for Text-to-SQL

Reference 23

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.480803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:cb2fa3e2793a8550a5eb944594dd4c6a99ccdc13b9bf06684a1219d0980ad77a

Observation e872f53e-0a4d-44c9-8712-bdb7daf48645 · outbound

This paper cites Hallucination Detection-Guided Preference Optimization for Clinical Summarization.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Hallucination Detection-Guided Preference Optimization for Clinical Summarization

Reference 24

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.600495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:5f80ad669870199b7f3cc0c2dda5de698d80a1f95b8fe48c03351a26c44805ca

Observation a3fa82e2-1ada-4cf6-bc33-458cd539e9d4 · outbound

This paper cites LongSumEval: Question-Answering Based Evaluation and Feedback-Driven Refinement for Long Document Summarization.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops LongSumEval: Question-Answering Based Evaluation and Feedback-Driven Refinement for Long Document Summarization

Reference 25

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.347538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:5dea33ed43af1006e972269aea8b48299ad178664d3638529f33a7b5d9e5e3f1

Observation b8aabc58-60e4-40d7-9685-c5e212272e99 · outbound

This paper cites LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots

Reference 26

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T03:45:55.447394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:00b5377ccc35433e081433a739ae263b116a54519a1bb8ff826481eb686c3051

Observation 27b2f90b-9240-410d-9fd1-0471a42b72b4 · outbound

This paper cites Adaptive self-improvement LLM agentic system for ML library development, 2025.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Adaptive self-improvement LLM agentic system for ML library development, 2025

Reference 27

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raw_fallback, observed 2026-07-09T03:45:55.849016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:ccd71344bdc2e1e5a1c7efb571b212decff3ed27f9276aeafdca29e405b19a70

Observation e6a2da08-af7f-463a-bdf3-898ad376c5c0 · outbound

This paper cites What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation

Reference 28

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.663975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0f96be4c4c3442fb83e9d6f5c2cb6d40542a47f169de59117557b2fd52f28739

Observation aab2b2be-88c8-4ea0-bfba-e2680564f015 · outbound

This paper cites Large Language Models Cannot Self-Correct Reasoning Yet.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Large Language Models Cannot Self-Correct Reasoning Yet

Reference 29

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local_arxiv, observed 2026-07-09T03:45:55.557536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:3562c15321d11e603af6f30824c7cb0e235f5290fcb7e61cd3c0d4018ec48519

Observation 123a3099-0f38-40cf-9adf-4be7f1243a11 · outbound

This paper cites When Does Intrinsic Self-Correction Help? A Task-Sensitive Analysis.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops When Does Intrinsic Self-Correction Help? A Task-Sensitive Analysis

Reference 30

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local_arxiv, observed 2026-07-09T03:45:55.368323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:59a688a47bf85697972d1037c071b6f2c40e7cf1a6861db761efa711429c5d64

Observation a3370c22-b701-4421-ad3a-9ca3a893be92 · outbound

This paper cites When are likely answers right? On Sequence Probability and Correctness in LLMs.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops When are likely answers right? On Sequence Probability and Correctness in LLMs

Reference 31

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local_arxiv, observed 2026-07-09T03:45:55.405342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0108beb315f80c6cca6bb832da2cd46c69a1821ab4595802c23911117393a36c

Observation a912db66-8e34-4b2c-90ca-5253683a8065 · outbound

This paper cites Ask, Don't Judge: Binary Questions for Interpretable LLM Evaluation and Self-Improvement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Ask, Don't Judge: Binary Questions for Interpretable LLM Evaluation and Self-Improvement

Reference 32

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verified exact
local_arxiv, observed 2026-07-09T03:45:55.408026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0fc061300162fcb65943a5c9833a74d2f7e8f5c748e5cf606cf12dff5423a1b4

Observation af829bae-ecfa-4227-8bfe-75bbb8b8c721 · outbound

This paper cites LL3M: Large Language 3D Modelers.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops LL3M: Large Language 3D Modelers

Reference 33

Resolution
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local_arxiv, observed 2026-07-09T03:45:55.353500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:1aae0105245f1d25d5c927e9ed93c9e2f2d7a9e32ea64e9e97f1ff95c5bbadd1

Observation 036b60f5-815f-4dc0-8ee3-10de6f56ff34 · outbound

This paper cites AgenticDB: Self-Evolving Reconfiguration Framework for Database Workloads.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops AgenticDB: Self-Evolving Reconfiguration Framework for Database Workloads

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.402229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:74a0ec0c66aa3cfaf7fac76cb2584c31b47c93b50053661d5a730e8aa6925c9a

Observation 644440da-1115-495f-8e49-d149af60d863 · outbound

This paper cites AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.729498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:effc81fd298007f7ac7458604931a2fb8d9b62358a4c5ea01728b24cbbcd52fb

Observation 98ec3737-b0e1-4ed2-9b53-f6be09825a2c · outbound

This paper cites LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.783221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:10d7eb7b9587bb60b360a4db099e4246170226fe232c013932232570eca8b905

Observation 70b3f501-cfbc-4b46-9863-e611af8d5dc5 · outbound

This paper cites KVerus: Scalable and Resilient Formal Verification Proof Generation for Rust Code.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops KVerus: Scalable and Resilient Formal Verification Proof Generation for Rust Code

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.374227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:c43d1d9606023f315faf56746355e84704b5208e8aaa9e7d8213e03e19514747

Observation f5c84150-cb27-4560-9629-fc8a5bfc669c · outbound

This paper cites KBSpec: LLM-driven Formal Specification Generation with Evolving Domain Knowledge Base.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops KBSpec: LLM-driven Formal Specification Generation with Evolving Domain Knowledge Base

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.414339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:92dba433b07a2f9be2aa519ec3e6969e269fbf9ceea27202903ce7b4e0d7f350

Observation f15f8a53-9eac-4afc-b011-fdda8f9d4f17 · outbound

This paper cites Verifier-Guided Code Translation via Meta-Step Decoding.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Verifier-Guided Code Translation via Meta-Step Decoding

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.327266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:70ec35c034620d180c66f9c931a80deed06077113d885df1dff58c2390b93396

Observation 3051e410-a2f5-466f-876c-82fdda679d8c · outbound

This paper cites What Drives Interactive Improvement from Feedback?.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops What Drives Interactive Improvement from Feedback?

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.331456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:8c8fc8154b6de393917c7fd36f8e182436b4f1a0f6d5098bdc85bfc156bda50e

Observation 67bbc434-8833-4e4f-88b6-3d2db08c4848 · outbound

This paper cites Falsification, Not Exposure: An Internally Preregistered Placebo-Controlled Decomposition of Self-Repair Feedback in Frozen Small Code Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Falsification, Not Exposure: An Internally Preregistered Placebo-Controlled Decomposition of Self-Repair Feedback in Frozen Small Code Models

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.393882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0919a788376f5d150a0cd7bb4f5f94a286b4aff38cff002d71bdb2eee7a9e330

Observation 76b3d871-8d98-4c49-803f-6374ed0157fa · outbound

This paper cites Feedback Over Form: Why Execution Feedback Matters More Than Pipeline Topology in 1-3B Code Generation.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Feedback Over Form: Why Execution Feedback Matters More Than Pipeline Topology in 1-3B Code Generation

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.621566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:159460761a425594949b1c78a9ef261683069128b38c37c2b2a5e115deea0ad8

Observation 26f04597-153e-416d-a8aa-8db17111137d · outbound

This paper cites RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.504061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:3dc9b6e947788d64a2ff97f0192f03d0118275658b875bc50b3af17cd1cf0623

Observation dfc7faa1-1530-419b-8931-a5e650f9186d · outbound

This paper cites Unlocking LLM code correction with iterative feedback loops,.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Unlocking LLM code correction with iterative feedback loops,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.876205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:3a563b749b81b16f2aa2f808e1a17a8cc3e4f161fb895767df79fc6de679141c

Observation 2dd0242c-8934-47a8-bb8f-c65d7787c58f · outbound

This paper cites Unlocking LLM Code Correction with Iterative Feedback Loops.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Unlocking LLM Code Correction with Iterative Feedback Loops

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.738891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:48f114df9b056e68118285dfc624367e49d60c542f52426b3ea7f18aec87256c

Observation 6bc72256-f1b6-4835-9614-0038e1c96d7f · outbound

This paper cites Denoising Iterative Self-Correction: Structured Verification Loops for Reliable LLM Reasoning.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Denoising Iterative Self-Correction: Structured Verification Loops for Reliable LLM Reasoning

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.778456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:b4a68e5a3d788c97b210c78df0a54e3ee4c6085e9ae2036c865c2d6d560d9fd1

Observation b91fceed-1a7b-4f12-a9e4-b04bab3fad30 · outbound

This paper cites FLARE: Fine-Grained Diagnostic Feedback for LLM Code Refinement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops FLARE: Fine-Grained Diagnostic Feedback for LLM Code Refinement

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.460460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:feeecd7779cd5fbc800fe4dd9b3284d09828d7a6065b128a38631fdd21ee9f48

Observation 3a28547e-a231-42ab-a013-21d8f9a9f3bc · outbound

This paper cites CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.545662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:4d0440b6bf09d4fc27d248e113c589828e0b4f45a7424013949cf1e24a4d34b1

Observation 78c28d50-a80e-48c0-a76d-688f49163fa2 · outbound

This paper cites Kestrel: Grounding self-refinement for L VLM hallucination mitigation, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Kestrel: Grounding self-refinement for L VLM hallucination mitigation, 2026

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-07-09T03:45:55.755947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:402da9f2be435c66241844eeb1bb310fd6015e22f4459c08d4f9e132e12f6223

Observation 68065f41-1cf3-45d5-a496-1145cca07d77 · outbound

This paper cites Reflect-R1: Evidence-Driven Reflection for Self-Correction in Long Video Understanding.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Reflect-R1: Evidence-Driven Reflection for Self-Correction in Long Video Understanding

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.592075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:618d58a6a3a72bad54954834b6258edf20351fdb0f4941e059734194bfaa1852

Observation a4ace666-7e0a-44c8-8f67-172b67eb5cfe · outbound

This paper cites FiRe: Fine-grained Multimodal Reasoning for Enhanced Image Generation.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops FiRe: Fine-grained Multimodal Reasoning for Enhanced Image Generation

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.776021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:f9909012b6d8c7df4efd2f7490e4080fab320708c4b699c1264f3a956f56e56c

Observation ffdef31b-766b-4a24-8f98-676bdd2f7572 · outbound

This paper cites Proprio: Latent Self-Scoring and Inference-Time Refinement for Physically Plausible Video Generation.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Proprio: Latent Self-Scoring and Inference-Time Refinement for Physically Plausible Video Generation

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.362766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:7a746c49d1cfcf3049383686d2395f5e3bf71da34f7a88afb1d7aa3eebb36c07

Observation 385107ae-06b9-49dd-8b87-19e965385ed6 · outbound

This paper cites ActiveScope: Actively Seeking and Correcting Perception for MLLMs.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops ActiveScope: Actively Seeking and Correcting Perception for MLLMs

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.704740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:dc50b9dc248844e51163514f8f97d185ea9ba48efd8e510fa87c34146aa03103

Observation d8721876-882d-4449-9eed-de890e10e47a · outbound

This paper cites Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.610831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:df0d43b96b36abbbfc879e61b2a553a8ee1df25c0b19f15958520c9b0bde23e5

Observation bf017190-862d-485f-adc5-5f7716aaf8ee · outbound

This paper cites Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.469759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:cfbaa6c7bcd629c31f6544022c700345ff648f7ff461c39464bdf34574d7caa7

Observation a6e5c862-e5b1-42d0-8c52-34c7bd603ed4 · outbound

This paper cites Personal Visual Context Learning in Large Multimodal Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Personal Visual Context Learning in Large Multimodal Models

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.384955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:3d46bef0b11451ad7d62813f4977dff0b52d520c825927986a2915aa0def138d

Observation b13de402-a511-4b9c-9cb1-ffef1cdc9121 · outbound

This paper cites Each Judge Its Own Yardstick: Discovering Per-VLM Taxonomies for Physical Video Evaluation.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Each Judge Its Own Yardstick: Discovering Per-VLM Taxonomies for Physical Video Evaluation

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.382139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:6bb375dcaf4f234e70b8c5ea720e85328b367ec682d3dad011b150e79287150c

Observation fecc52f1-aec6-4e09-ac33-b2446e68f467 · outbound

This paper cites Query-conditioned test-time self-training for large language models, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Query-conditioned test-time self-training for large language models, 2026

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.890641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:08cc3a49c9d25a3dd77a8136cf4f030ee08e8ef847554e49b2ee75a30d04586e

Observation 00d8d9bf-4441-4ac4-9ff2-b3b4e19aa9c9 · outbound

This paper cites Continual Self-Improvement with Lightweight Experiential Latent Memories.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Continual Self-Improvement with Lightweight Experiential Latent Memories

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.571939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:d21cd54e41ad718d862a09692782e39d25b47385d2e93bfa7d32512ae8aeaf71

Observation 2fecb2b9-89b5-4fec-9247-52f5518e5d0d · outbound

This paper cites Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.597811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e14e40570e11b354fea3c9aa90f31a9d58f9c1ed150d304b2b6caadaa4999ed0

Observation 1e3ff57d-18da-485b-b977-6daeef297033 · outbound

This paper cites Truly Self-Improving Agents Require Intrinsic Metacognitive Learning.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Truly Self-Improving Agents Require Intrinsic Metacognitive Learning

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.365517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:96629f18a5cb8ec5f74a40184ce3db6196197ddcfc75a81d90564e90b97b2a57

Observation 3392d613-f5c6-4451-a386-f4ae655efec7 · outbound

This paper cites Environment-Grounded Automated Prompt Optimization for LLM Game Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Environment-Grounded Automated Prompt Optimization for LLM Game Agents

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.780878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:74430f0918ebee2fc585b0ac58a898cc1670cc6a5155238ea6bf51d94855b463

Observation c513d312-eab5-4b6a-9e8b-b56cbce3139b · outbound

This paper cites Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.589146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:d46bcf573fdcaf147209a39f350de0cb265548c9c418d62a5dd7020168288c46

Observation 43775fb4-66a1-412a-a74a-89af095e2273 · outbound

This paper cites The Red Queen G\"odel Machine: Co-Evolving Agents and Their Evaluators.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops The Red Queen G\"odel Machine: Co-Evolving Agents and Their Evaluators

Reference 64

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T03:45:55.542552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:b724ac03d5ad397a15e4d6a8d3ba272298710cf3cbbb877a53db34411efcfe57

Observation 08494592-21af-4258-b241-1fb074f9bf12 · outbound

This paper cites Sc.) Yang.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Sc.) Yang

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.888879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:53402ed5cb873d4ee1212d582ce037b816ab298cd893e2ebdf5f1a2057da320b

Observation 543204a5-c8b4-4720-a60f-7f6cb2299f8b · outbound

This paper cites QueenBee Planner: Skill-Evolving Communication Topologies for Token-Efficient LLM Multi-Agent Systems.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops QueenBee Planner: Skill-Evolving Communication Topologies for Token-Efficient LLM Multi-Agent Systems

Reference 66

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.712618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:c56f901886dfeffc2f12af8a11f4146e567c3cea9b2a6d9d0a062f40d6cd53ff

Observation fe97aaba-40e3-4095-b6a1-251cba9aa7b0 · outbound

This paper cites Learning from Failure: Inference-Time Self-Improvement for Computer-Use Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Learning from Failure: Inference-Time Self-Improvement for Computer-Use Agents

Reference 67

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.388063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e190e9ca26cd9182ac6df1407b6b2e92423add1d461efc5137e42731361b261b

Observation bae873d4-074d-40f7-aaaa-351250de3836 · outbound

This paper cites Experience Graphs: The Data Foundation for Self-Improving Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Experience Graphs: The Data Foundation for Self-Improving Agents

Reference 68

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.435691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:81769730e22601c59c0590d451a6501b284d9f1d0212ca9b712522e96ea20460

Observation c37c90ef-bcf3-4b4c-be05-e182593789a5 · outbound

This paper cites The meta-agent challenge: Are current agents capable of autonomous agent development?, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops The meta-agent challenge: Are current agents capable of autonomous agent development?, 2026

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.860156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:574bbf8143587ac787fe07ffaea3f0652e2f31a89fa4bec348bd673e06159418

Observation 918b8024-0878-4f7e-9a0a-ab652bdc3238 · outbound

This paper cites SAGE: A quantitative evaluation of socialized evolution in agent ecosystems, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SAGE: A quantitative evaluation of socialized evolution in agent ecosystems, 2026

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.880029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0b187e7e0bba027296ff8ac045c3d5f1b36071784a2940077c02067992fc945a

Observation 532cbc44-7530-4413-97c4-723818559cab · outbound

This paper cites Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling

Reference 71

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.536724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:217e73e8e807056a08677e77ad1804ea144a3e2ff375247bd66e420388ded4eb

Observation 9e08a5e0-49a1-4228-95d1-b525d8ab4f80 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 72

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.647523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:88ba1428072b3f83aa87ffc075028ff71c045b643b6fcc54d7d9af318202a53d

Observation 69bd13eb-2b1d-49ac-a857-a095c6144429 · outbound

This paper cites SkillAxe: Sharpening LLM-Authored Agent Skills Through Evaluation-Guided Self-Refinement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SkillAxe: Sharpening LLM-Authored Agent Skills Through Evaluation-Guided Self-Refinement

Reference 73

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.586334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:445d0cd262fd8173fecb94801b29217ab15f311229621da3e7a49ce2c538040e

Observation 64078c97-1cb0-4eb7-b70c-15dd90ce9b12 · outbound

This paper cites Skill-R1: Agent Skill Evolution via Reinforcement Learning.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Skill-R1: Agent Skill Evolution via Reinforcement Learning

Reference 74

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T03:45:55.417470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:59653952699848478e155b4c67d2a7f7bf2728a8011729da67fef2dd139c636c

Observation 57d0a835-f9ce-48f8-a932-00ec0a3f9521 · outbound

This paper cites SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision

Reference 75

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.376945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e5f53f0da5dd3fe29196254590831f296e2d107e164625237a9cfe3e05b793d2

Observation 448c7e51-ec6c-42c5-bf64-8292882bd958 · outbound

This paper cites AlgoSkill: Learning to Design Algorithms by Scheduling Human-Like Skills.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops AlgoSkill: Learning to Design Algorithms by Scheduling Human-Like Skills

Reference 76

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.684552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e6bb253fe37fef9b15ba3e2a7bcf1d18984f73b97c302b33f3fe9041ddfea3c0

Observation bbeadfd5-a759-4c5f-b6cd-4f3d34323bb9 · outbound

This paper cites SkillMaster: Toward Autonomous Skill Mastery in LLM Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SkillMaster: Toward Autonomous Skill Mastery in LLM Agents

Reference 77

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.637652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:dda8db930560925f624a23c63cd535acde21fa960f69ed41fa7bb11eecef1c78

Observation 96eb4a80-d5c2-48b0-b021-95d1bec016b5 · outbound

This paper cites FederatedSkill: Federated Learning for Agentic Skill Evolution.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops FederatedSkill: Federated Learning for Agentic Skill Evolution

Reference 78

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.642671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e16fd50cf9aaa3e1df6010acbfc6ba75bcc6f703dff04269018db1b7381a1e76

Observation 35bdcda2-1e37-4b8e-ab92-951d0d0e6437 · outbound

This paper cites SkillSmith: Co-Evolving Skills and Tools for Self-Improving Agent Systems.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SkillSmith: Co-Evolving Skills and Tools for Self-Improving Agent Systems

Reference 79

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.722234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:431c1df907d70e87d28a951c1361c975b1b92b8f1f522d02223523cf8ed87bb3

Observation 8580d7b7-eb70-4d7e-9351-6045a50e5ec6 · outbound

This paper cites Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills

Reference 80

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.717442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:0ae11af11f72632c63c1be7b99d496bcb8ed3a3327e31ec3e405113d54460a2f

Observation 9e835dfa-2a5c-4c45-88eb-19e8fc8af797 · outbound

This paper cites SHARP: A Self-Evolving Human-Auditable Rubric Policy for Financial Trading Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SHARP: A Self-Evolving Human-Auditable Rubric Policy for Financial Trading Agents

Reference 81

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.652368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:edffe9b72655aa641e04aa56f46ccd2629881ca7850be36be68dbb74a40633e3

Observation 728cc8bb-e18b-4337-ab4c-392181cabd8e · outbound

This paper cites SkillMutator: Benchmarking and defending language-and-code cross-modal attacks on LLM agent skills, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SkillMutator: Benchmarking and defending language-and-code cross-modal attacks on LLM agent skills, 2026

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-07-09T03:45:55.607223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:86e636e3d470fb2ae7486c41ecff18301c8bbab5989d14f969601806e7d61ee9

Observation 4aa2734b-6e02-4619-8040-3265ebd7eb81 · outbound

This paper cites SkillHarness: Harnessing Safe Skills for Computer-Use Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SkillHarness: Harnessing Safe Skills for Computer-Use Agents

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.580414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:901a9d2a88c711f4a12bb84afbc591c2b0cf6d468270c9f30ea65255308b7e18

Observation 6cfbc72c-dd20-4aa1-996b-b24787a894f9 · outbound

This paper cites VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents

Reference 84

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T03:45:55.656822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:90024a72f3ead603ff9424abe48aeb3eeb0cb5d106fd58db74d1d6eb15100d6b

Observation e1b4cef2-3307-4b53-b8fe-e8409733b8f6 · outbound

This paper cites Safety in Self-Evolving LLM Agent Systems: Threats, Amplification, and Case Studies.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Safety in Self-Evolving LLM Agent Systems: Threats, Amplification, and Case Studies

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.634851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:b542a55d25dee703c03f2072f9e3f89bd650518cba34f4a3952455e865daaf28

Observation 86869a38-534c-4d0e-8a5b-946acae246bd · outbound

This paper cites Towards Healthy Evolution: Exploring the Role and Mechanisms of Human-Agent Interaction in Self-Evolving Systems.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Towards Healthy Evolution: Exploring the Role and Mechanisms of Human-Agent Interaction in Self-Evolving Systems

Reference 86

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.475665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:7cecd325c8d55a8b7ef42e33f47d664cc8234e87b853b38c6cba48a1807bf94f

Observation 327a5ae8-dbd3-427a-ad6a-8f2b1bf6a204 · outbound

This paper cites Co-Reyes, Rishabh Agarwal, et al.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Co-Reyes, Rishabh Agarwal, et al

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.847181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:df9920d7030ea33fc739e3db36c6565baf603de0e6af25d094e8a3e06095cf93

Observation a9c370f1-2fbc-4c4e-b52a-fc9983e517b4 · outbound

This paper cites Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Reference 88

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.613579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:1ac95efc65114eed43a9a4fba4e8c2e19216d2a96e2343ed2662127ab0812dab

Observation d5ea40c1-a14f-41a6-8463-a32c16913dd9 · outbound

This paper cites ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Reference 89

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.624038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:ec8b041e0f533c80944b09a96e485c3b3104bef2523935fa206e6eba7538bab8

Observation 269bbb38-c485-4f12-a941-d737465ff684 · outbound

This paper cites SEVA: Self-Evolving Verification Agent with Process Reward for Fact Attribution.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops SEVA: Self-Evolving Verification Agent with Process Reward for Fact Attribution

Reference 90

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.569273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:cfc63446d87ac9476bba27ec062a5be6acaaf3d5b0a2d7a6a07e8ce3b163b0fc

Observation c28d8365-394d-49be-825e-6e454133415b · outbound

This paper cites EvoIdeator: Evolving scientific ideas through checklist-grounded reinforcement learning, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops EvoIdeator: Evolving scientific ideas through checklist-grounded reinforcement learning, 2026

Reference 91

Resolution
verified exact
arxiv_id, observed 2026-07-09T03:45:55.411227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e25c872f09c30831926f44552a0f580dc02a1139fb926d91ae3089f94a02fc49

Observation 5fc4ad16-0326-49fe-8790-14cc8e03fe5a · outbound

This paper cites Retrospective progress-aware self-refinement for LLM agent training, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Retrospective progress-aware self-refinement for LLM agent training, 2026

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-07-09T03:45:55.626889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:6c88a1d6055e3e990386d2a36cc3d7ac3df7930b3cd8682eb813e0487137fcd8

Observation 3c8b8292-a30f-40a8-b3d0-ff60fe362ed0 · outbound

This paper cites The value axis: Language models encode whether they’re on the right track, 2026.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops The value axis: Language models encode whether they’re on the right track, 2026

Reference 93

Resolution
verified exact
arxiv_id, observed 2026-07-09T03:45:55.619007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:ff56b8eabb8c034a40badfa3d74844653da8c0b2c061adcab375e3e9c3edb337

Observation ab8cdbd4-d068-445f-851f-11d30965313b · outbound

This paper cites Self-Trained Verification for Training- and Test-Time Self-Improvement.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Self-Trained Verification for Training- and Test-Time Self-Improvement

Reference 94

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.527822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:4ac32dd1a4f4a26b0772ebca6f4f1be89f091c5b048efa491d80a7a3a9c51d72

Observation 9464d382-33b3-4475-bdc9-51ca0acae61f · outbound

This paper cites Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training

Reference 95

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.371267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:2da545bbaabca4f01f00da6498ab65d17617280eeed2742ab6d1db1287b54b01

Observation 182584ca-5e46-426e-a268-0f8f0e5f71e9 · outbound

This paper cites When LLM Reward Design Fails: Diagnostic-Driven Refinement for Sparse Structured RL.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops When LLM Reward Design Fails: Diagnostic-Driven Refinement for Sparse Structured RL

Reference 96

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.320802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:94d5ec95a2e4e9cbef7e9f12c197d253d50437cffc764e16ea79f38513837b59

Observation 455786b4-2d1d-4425-859e-4b25003b55bb · outbound

This paper cites Repeated post-training is not self-improving: Diagnosing scientific amnesia in continual DPO pipelines,.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Repeated post-training is not self-improving: Diagnosing scientific amnesia in continual DPO pipelines,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.883705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:9c959fe6cc0abbeb6b709881a8a86483496e8f9a823de7e82fa416aed2aadb53

Observation 33730790-45f5-46b6-8449-658ff1ca253e · outbound

This paper cites Repeated post-training is not Self-improving: Diagnosing Scientific Amnesia in Continual DPO Pipelines.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Repeated post-training is not Self-improving: Diagnosing Scientific Amnesia in Continual DPO Pipelines

Reference 98

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.399431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:f8489c739c6d31e7188cb9285a3cbedc044e597d8b2d22abe092346d90916ac8

Observation 4f30db50-85eb-469b-9b06-b2b45f16cf22 · outbound

This paper cites Re-ReST: Reflection-reinforced self-training for language agents, 2024.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops Re-ReST: Reflection-reinforced self-training for language agents, 2024

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T03:45:55.881892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:e5a6fb3e56f0e4ba92b920ae177bb27f9d57d47347f745a9b60cf585bc4d11d2

Observation 5fb69b4c-d12f-4e0b-b557-bd89596271da · outbound

This paper cites PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking.

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking

Reference 100

Resolution
verified exact
local_arxiv, observed 2026-07-09T03:45:55.510480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T03:36:57.168246Z digest=sha256:22ab69d22b2a973ac9791bc88dcc13d5017d6ffda061c0db74aa529729a77b83

Pith citing papers

Observation 3edcfe75-972c-435b-9a0d-84a392562412 · inbound

The Calibration Floor: Format Repair Can Masquerade as Self-Correction at Small-to-Mid Scale cites this paper.

The Calibration Floor: Format Repair Can Masquerade as Self-Correction at Small-to-Mid Scale Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-08T19:13:05.886833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-08T19:13:05.287776Z digest=sha256:ade887c1accde291476fcb5e73ccbadc67ee349557b87477112f3af495dd7b84

Observation 495abdf0-ba25-461b-9bfa-39dccef6eade · inbound

The Horizon Gap: Planning, Memory, Execution, Training, and Evaluation for Long-Horizon LLM Agents cites this paper.

The Horizon Gap: Planning, Memory, Execution, Training, and Evaluation for Long-Horizon LLM Agents Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T23:01:35.509270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:01:35.509270Z digest=sha256:d9a7abdce67c8b4882feb1e278e7bba39d8c0166c98b700a80a8fa617b379ba7

Observation 2b94b6b5-95a5-465f-b1be-3a32ee14a82a · inbound

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA cites this paper.

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-11T10:20:58.764730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:20:58.764730Z digest=sha256:9cec05a69fd28e0c446302a8a376190f9987f94e0ab5f99fa49acff1df060196