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Paper Citation Record · LEDGER

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

As of 21 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 27 inbound Pith citation observations for arXiv:2506.16499.

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

pith.paper-citation-record.v1
2506.16499 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:28:27.573180Z

measured 78 of 78 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:25:16.606463Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

51 of 51 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved36
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation eb7bb538-cd97-45bf-86d0-5ed3d2c91f05 · outbound

This paper cites Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, Hoang H.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, Hoang H

Reference 1

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Observation 6a5bf641-a685-4652-89fd-0ad71f5b8836 · outbound

This paper cites Aide: Ai-driven exploration in the space of code, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Aide: Ai-driven exploration in the space of code, 2025

Reference 2

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Observation d1ef53d5-0fcb-45f8-87c4-cbb00f902b0b · outbound

This paper cites R&d-agent: Automating data-driven ai solution building through llm-powered automated research, development, and evolution.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning R&d-agent: Automating data-driven ai solution building through llm-powered automated research, development, and evolution

Reference 3

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Observation 071b0ff9-c393-41f5-8320-fbb436c7ed84 · outbound

This paper cites MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

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source=pdf_text observed=2026-08-15T19:28:26.761875Z digest=sha256:9a153301746f4866d84e728e6087a94e431143c940d555e1b84a85cea859bbbf

Observation b7786754-0310-4180-9a02-e1ed8f8399c5 · outbound

This paper cites Economic impacts of artificial intelligence (ai), 2019.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Economic impacts of artificial intelligence (ai), 2019

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 0d3a300d-af39-4a96-bd56-382787298203 · outbound

This paper cites The economic impact of artificial intelligence in health care: systematic review.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning The economic impact of artificial intelligence in health care: systematic review

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation ea5cc7f8-28c5-4ef2-abf6-0b1d695b9a84 · outbound

This paper cites Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations

Reference 7

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Observation 04ebcbd1-ba8e-4753-86da-48066ab71261 · outbound

This paper cites Navigating the confluence of artificial intelli- gence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Navigating the confluence of artificial intelli- gence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7bbc7fa9-bf43-4d75-977c-13e908b0510b · outbound

This paper cites an unresolved cited work.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Unresolved cited work

Reference 9

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Observation 2f5ad71f-2cd8-44c2-b7c7-148fd50fbdde · outbound

This paper cites Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas L.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas L

Reference 10

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Observation b9b8954e-6ba5-4704-aeb4-4c1eb20c7cff · outbound

This paper cites Mastering the game of go with deep neural networks and tree search.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Mastering the game of go with deep neural networks and tree search

Reference 11

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Observation ced0b4ff-307c-417a-9c68-0dc4f250e87b · outbound

This paper cites A general reinforcement learning algorithm that masters chess, shogi, and go through self-play.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning A general reinforcement learning algorithm that masters chess, shogi, and go through self-play

Reference 12

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source=pdf_text observed=2026-08-15T19:28:26.803808Z digest=sha256:0def6cc0f507bc130734ed778ec402c3da2fff900f0b0acb8db6cd0ede29c0eb

Observation 02ae27d4-328d-4806-b66c-64212fb5109c · outbound

This paper cites Introducing openai o1.https://openai.com/o1/, 2024.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Introducing openai o1.https://openai.com/o1/, 2024

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9e040612-b716-4ad3-a180-613b8c250a01 · outbound

This paper cites System card: Claude opus 4 & claude sonnet 4, 2024.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning System card: Claude opus 4 & claude sonnet 4, 2024

Reference 15

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation a1755caf-6444-477b-8e32-beb4758b45a2 · outbound

This paper cites AutoML-GPT: Automatic Machine Learning with GPT.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning AutoML-GPT: Automatic Machine Learning with GPT

Reference 16

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Observation 23176603-0e85-4754-8e1c-b31c5931cdd6 · outbound

This paper cites Deepresearcher: Scaling deep research via reinforcement learning in real-world environments, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Deepresearcher: Scaling deep research via reinforcement learning in real-world environments, 2025

Reference 17

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Observation 34824cb5-de79-4e71-b5e7-f893702f40aa · outbound

This paper cites Agent laboratory: Using llm agents as research assistants, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Agent laboratory: Using llm agents as research assistants, 2025

Reference 18

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Observation d3c0549c-2cec-4c64-b31d-36f2a84fe15c · outbound

This paper cites The ai scientist: Towards fully automated open-ended scientific discovery, 2024.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning The ai scientist: Towards fully automated open-ended scientific discovery, 2024

Reference 19

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Observation 98fbea0e-2695-4211-91d1-08890414adf0 · outbound

This paper cites SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning

Reference 20

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source=pdf_text observed=2026-08-15T19:28:26.851909Z digest=sha256:a59d8e78f22f91db291f2d1e94f3f1c96e3f0ac540d6fcf35615bac8b6fac631

Observation 824bc8cf-a92d-44e2-b1bf-97ae87bf6406 · outbound

This paper cites MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Reference 21

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source=pdf_text observed=2026-08-15T19:28:26.876986Z digest=sha256:92ca798fda9d061071c7bfabd977c3b0fa9b251b77c21ddcdc272848b48a7e4d

Observation b7024376-bbb0-456d-a22e-2db002f7c91d · outbound

This paper cites Dolphin: Moving towards closed-loop auto-research through thinking, practice, and feedback, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Dolphin: Moving towards closed-loop auto-research through thinking, practice, and feedback, 2025

Reference 22

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 0afa01b9-44ab-47cb-b583-2e792599d353 · outbound

This paper cites Paper2code: Automating code generation from scientific papers in machine learning, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Paper2code: Automating code generation from scientific papers in machine learning, 2025

Reference 23

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Observation b99a8dae-89ab-4f5a-8bea-5100103504b9 · outbound

This paper cites The second half.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning The second half

Reference 24

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9f8ab69c-8756-4fcb-bf0d-79715233732b · outbound

This paper cites AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

Reference 25

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Observation 97b11b4a-d09e-41ae-b669-e5c45441071b · outbound

This paper cites Tpot: A tree-based pipeline optimization tool for automating machine learning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Tpot: A tree-based pipeline optimization tool for automating machine learning

Reference 26

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Observation d03d073e-39a7-4b63-a9b0-d3dc0066fb23 · outbound

This paper cites Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

Reference 27

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source=pdf_text observed=2026-08-15T19:28:27.082888Z digest=sha256:a0864a70d5eb0caf257fff0e9e16ced6fb691e87f3b1048eecb0d1fe90478fcd

Observation bae256ff-f459-4750-844c-b48d3904d328 · outbound

This paper cites Ml-plan: Automated machine learning via hierarchical planning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Ml-plan: Automated machine learning via hierarchical planning

Reference 28

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raw_fallback, observed 2026-08-15T19:28:28.629264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 6c9f445e-1760-4450-84c4-1734d1f19107 · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 29

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Observation 39160af8-64be-4002-bf2f-7b51f80fbd90 · outbound

This paper cites An admm based framework for automl pipeline configuration.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning An admm based framework for automl pipeline configuration

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 363e0673-da7f-48e1-92ef-00fe51327b5a · outbound

This paper cites Automated Machine Learning with Monte-Carlo Tree Search.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Automated Machine Learning with Monte-Carlo Tree Search

Reference 31

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Observation e876a72d-dd33-4677-b0bf-585eb2995404 · outbound

This paper cites DARTS: Differentiable Architecture Search.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning DARTS: Differentiable Architecture Search

Reference 32

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source=pdf_text observed=2026-08-15T19:28:27.126701Z digest=sha256:d95b8f340910c047ffad21fdcc49a461e4f905dfc319922446200c31c82a9685

Observation 66500e64-32ee-4ed5-a8bc-4d59fc6afdff · outbound

This paper cites AutoML-Zero: Evolving Machine Learning Algorithms From Scratch.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning AutoML-Zero: Evolving Machine Learning Algorithms From Scratch

Reference 33

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Observation 1fa7b327-c2f5-4687-a0ad-eb5187ecc4bc · outbound

This paper cites Learning transferable architectures for scalable image recognition.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Learning transferable architectures for scalable image recognition

Reference 34

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source=pdf_text observed=2026-08-15T19:28:27.139288Z digest=sha256:e0193aefa73a657b82f9ce30405306c16940cc2a1a1fb3bd461f0cf656c50447

Observation d24b735d-f1f3-468d-91ec-7ccd891d7a83 · outbound

This paper cites Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search

Reference 35

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation b5c704d6-24ff-46b4-9182-2eac70da6a90 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 36

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source=pdf_text observed=2026-08-15T19:28:27.151763Z digest=sha256:6febb64ba6801058d3cb4c4e05962218ea7ba1816274e67d52b950c2f63022e4

Observation f5fe4a12-53fe-4bb5-821c-da6272d1873c · outbound

This paper cites Re- act: Synergizing reasoning and acting in language models.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Re- act: Synergizing reasoning and acting in language models

Reference 37

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source=pdf_text observed=2026-08-15T19:28:27.160488Z digest=sha256:658d126e8d3913af39cc50dcf3af259bba9adf485077af6eb9de74e373d44d3c

Observation a0cc4d1d-8afc-45d0-a26e-d98751e73f6f · outbound

This paper cites Qwen2.5-Coder Technical Report.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Qwen2.5-Coder Technical Report

Reference 38

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source=pdf_text observed=2026-08-15T19:28:27.166264Z digest=sha256:b9b35861bfb69a9b977ac92aa99b7fb0b622d881bf0cebb1e8e5fd141ac49cb8

Observation 31c0de53-121a-49ae-bbb0-42a42f0dd9ad · outbound

This paper cites MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks

Reference 39

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source=pdf_text observed=2026-08-15T19:28:27.173463Z digest=sha256:0e586531731d7306cff49b62a92565750af6581e2aa3be8da91b4b382820a8e6

Observation 4d1ef0bc-5e82-4786-8628-28384b25c861 · outbound

This paper cites AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions

Reference 40

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no resolver link, observed 2026-08-15T19:28:27.208931Z

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source=pdf_text observed=2026-08-15T19:28:27.208931Z digest=sha256:5a2d449ec335e30068157a27cc6e8db81460a6bdb3d4ff8fbd070adf153803ed

Observation 59c6076d-7ad4-4c7c-a9cb-efdf25bc4b63 · outbound

This paper cites Large language models orchestrating structured reasoning achieve kaggle grandmaster level, 2024.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Large language models orchestrating structured reasoning achieve kaggle grandmaster level, 2024

Reference 41

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raw_fallback, observed 2026-08-15T19:28:28.535519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T19:28:27.243360Z digest=sha256:6046af9425665001b1ff7ed2e48d64e8ac9cd09cd49727f6e99a3d3c6bdb85a3

Observation d2673bba-c711-4404-942e-9786678d1f23 · outbound

This paper cites Mlzero: A multi-agent system for end-to-end machine learning automation, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Mlzero: A multi-agent system for end-to-end machine learning automation, 2025

Reference 42

Resolution
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raw_fallback, observed 2026-08-15T19:28:28.418889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T19:28:27.298184Z digest=sha256:d93b8228776ad3ecc0cd03215b7f5ceee41c9a10c72a74d0d72e56247226913c

Observation 5b9671f7-7eea-41e9-8b86-596c976faaad · outbound

This paper cites Novelseek: When agent becomes the scientist – building closed-loop system from hypothesis to verification, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Novelseek: When agent becomes the scientist – building closed-loop system from hypothesis to verification, 2025

Reference 43

Resolution
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raw_fallback, observed 2026-08-15T19:28:28.286708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T19:28:27.354869Z digest=sha256:5a1eac1784fba53c4c60ec24145ac6c9831de5e4c24f6d82cfb486059f07e0de

Observation 9400d726-a22d-49af-98d9-68eba5b4c5eb · outbound

This paper cites Ai-researcher: Autonomous scientific innovation, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Ai-researcher: Autonomous scientific innovation, 2025

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:28:28.205017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T19:28:27.404112Z digest=sha256:2c3d79df26bbfe3b1b34546fa22aded1bdd351359bf42b0ac5741378583c5b19

Observation 5bf94a39-89dc-4d6b-abb3-6fb732fe9a12 · outbound

This paper cites Star: Self-taught reasoner bootstrapping reasoning with reasoning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Star: Self-taught reasoner bootstrapping reasoning with reasoning

Reference 45

Resolution
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no resolver link, observed 2026-08-15T19:28:27.458360Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:28:27.458360Z digest=sha256:d493d0fee85d82c5d5f7c2d92e04685190d18619e5aef922d4a20e8f53b874fb

Observation 899886cb-96d8-458c-b744-88883ae28ed6 · outbound

This paper cites rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 46

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no resolver link, observed 2026-08-15T19:28:27.531304Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:28:27.531304Z digest=sha256:8d662c621105a4f80e802de091159e4d23bc35e1d7a7b3046d325d35975e2192

Observation b56149ff-72ec-4d68-9260-0d8720042cc0 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning, 2023.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Reflexion: Language agents with verbal reinforcement learning, 2023

Reference 47

Resolution
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no resolver link, observed 2026-08-15T19:28:27.538014Z

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source=pdf_text observed=2026-08-15T19:28:27.538014Z digest=sha256:334b9bad02ffbad7db8fa4bdce1ecc6c4eda69d8c0686bb1a729dc41d2876586

Observation 931b5620-baa9-4a0a-8a74-4a52cd545d21 · outbound

This paper cites Self-Evolving Multi-Agent Collaboration Networks for Software Development.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Self-Evolving Multi-Agent Collaboration Networks for Software Development

Reference 48

Resolution
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no resolver link, observed 2026-08-15T19:28:27.547471Z

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source=pdf_text observed=2026-08-15T19:28:27.547471Z digest=sha256:0616ea0d756d7bcb00225b6f5239989fe6da3664ebeb166ad44919c1b1745823

Observation 1ac89be0-da4b-490b-9fe7-81e80ef60cfc · outbound

This paper cites Alita: Generalist agent enabling scalable agentic reasoning with minimal predefinition and maximal self-evolution, 2025.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning Alita: Generalist agent enabling scalable agentic reasoning with minimal predefinition and maximal self-evolution, 2025

Reference 49

Resolution
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no resolver link, observed 2026-08-15T19:28:27.556123Z

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source=pdf_text observed=2026-08-15T19:28:27.556123Z digest=sha256:698cde78917a75649f58275ddcb10aa3b584c91aec36a31070450bdf3fcc4112

Observation 17d20baa-90fd-4c05-a94d-e0f51339143c · outbound

This paper cites WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Reference 50

Resolution
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no resolver link, observed 2026-08-15T19:28:27.562193Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:28:27.562193Z digest=sha256:4f6e6a69255c86c336cc8c74b9e1a70764d4c4ab7aef981d8ca19c5cde9a579c

Observation dcc5011d-1568-490d-89b3-db39f3cd2bf9 · outbound

This paper cites AgentGym: Evolving Large Language Model-based Agents across Diverse Environments.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning AgentGym: Evolving Large Language Model-based Agents across Diverse Environments

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T19:28:27.567237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:28:27.567237Z digest=sha256:08281149d2f2b24f402390b89888d5c216fc5f89719b714ac8e282f21f1b5ab6

Observation bcc13192-ba34-4adb-bd49-5f85ed8f2e7e · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 52

Resolution
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no resolver link, observed 2026-08-15T19:28:27.573180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:28:27.573180Z digest=sha256:345a00f8bd1ccc9265824d4ca3b7b759be086a8c2fd5f0ec269e62d70df78649

Pith citing papers

Observation 678ba9ab-2ace-4012-82d7-40dfbdfb81e3 · inbound

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems cites this paper.

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:22:51.753127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T22:22:19.478156Z digest=sha256:3253336c2b4e4c2fd88fcd26bb779da5aa771a612da058676894e530af77cc85

Observation ab98348c-a87d-454a-ae3c-869c35827f01 · inbound

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining cites this paper.

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T18:11:42.722329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T18:09:18.157131Z digest=sha256:36251865188734b3e567558d0b78b9e8ece315db0cdf24aae96857788b4fef06

Observation 582e3f82-0839-4547-9f98-4c7b287c19a4 · inbound

NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines cites this paper.

NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:20:28.733190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-25T07:17:42.867555Z digest=sha256:744ff6d19ff250a31c425539193e10b1a16084f4f968aa37785366c30fcf2fb5

Observation af92d439-afa6-4569-94cf-8cefb0d164d3 · inbound

SciDER: Scientific Data-centric End-to-end Researcher cites this paper.

SciDER: Scientific Data-centric End-to-end Researcher ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 43

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no resolver link, observed 2026-08-02T19:41:51.972083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:41:51.972083Z digest=sha256:a968033aac1a36ca8a88e26f3337c9e61e39e100e3ced63e14c9109240d2eb9b

Observation 2a4574c1-f0aa-422b-96a7-fb020fc66d1a · inbound

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search cites this paper.

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 19

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verified exact
arxiv_id, observed 2026-05-15T17:50:12.279869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T17:49:46.383559Z digest=sha256:9d1d9e44f2ed249c888599c7c3db678b046329c83da1352b202987fa1e1e7074

Observation 763a5f28-b648-4e5f-a25b-2e03ef785509 · inbound

Multivariable Painleve'-II equation: connection formulas for asymptotic solutions cites this paper.

Multivariable Painleve'-II equation: connection formulas for asymptotic solutions ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 35

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no resolver link, observed 2026-07-13T20:15:09.462061Z

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source=pdf_text observed=2026-07-13T20:15:09.462061Z digest=sha256:643d7a44fe037dd3a3a336cf04973bd817cf7894c10fb96d5dbc27d73d5e37a8

Observation 301c0128-c994-4f71-a9c7-66cc4a9d540c · inbound

AIRA_2: Overcoming Bottlenecks in AI Research Agents cites this paper.

AIRA_2: Overcoming Bottlenecks in AI Research Agents ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 15

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metadata mismatch
arxiv_id, observed 2026-05-14T23:08:14.613791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-14T23:06:39.545404Z digest=sha256:32e0cd257175268e70e1ef756a6bc74f0c87daa970c4a13a81614b8162f9011e

Observation 3211e3e3-a6f5-4c0c-9d17-2ad6a56cc336 · inbound

Toward Autonomous Long-Horizon Engineering for ML Research cites this paper.

Toward Autonomous Long-Horizon Engineering for ML Research ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:46:08.182841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-10T15:50:20.550969Z digest=sha256:ac94dd8a05522277299ceb7e7c01c8cd123ed3472c8679a130a0b5a6be77ede1

Observation 4c2c476a-57ec-4d5f-8cf6-9d486125ad1e · inbound

Toward Autonomous Long-Horizon Engineering for ML Research cites this paper.

Toward Autonomous Long-Horizon Engineering for ML Research ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 11

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no resolver link, observed 2026-07-12T21:01:34.659347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T21:01:34.659347Z digest=sha256:e86393820343671cc8f538b7c04066168e9288e8bfe1aa1153616a26da5439ff

Observation 998811d5-7984-4514-ad4f-4f085c88717f · inbound

AIBuildAI: An AI Agent for Automatically Building AI Models cites this paper.

AIBuildAI: An AI Agent for Automatically Building AI Models ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 27

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verified exact
arxiv_id, observed 2026-05-10T12:50:24.862925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T12:49:09.813157Z digest=sha256:44497e919f27ef2b969e30f361d2169bfe92b82cd62e7a9df8397a802e9c6503

Observation 51a755c4-fefa-412d-bd98-f482592c1c9a · inbound

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale cites this paper.

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 7

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verified exact
arxiv_id, observed 2026-05-10T06:01:13.380224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T05:59:01.010437Z digest=sha256:03f4ae5384dd106cbfc9699470fa2fff31a43ab0fcfd7d7d96f973343f5c296e

Observation bd13f54d-76bd-4d8b-8ca5-55893764e829 · inbound

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale cites this paper.

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-07-05T17:51:14.780830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-05T17:45:55.631459Z digest=sha256:dd20c5c87aac07f5016a0d1492da166271561c7c64d96010e6baa09cf00b4af0

Observation 949e964f-646a-4cab-b2cb-ae1cb73627b6 · inbound

SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning cites this paper.

SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T17:01:08.428146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-09T14:18:14.048230Z digest=sha256:7c8b7ac748104b02353ddb6c2846d8b341a3b1731c6dc05c5289b6efe62c8c2f

Observation 7848622e-45e8-4157-b0e7-429dfd86ee46 · inbound

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows cites this paper.

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 16

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verified exact
arxiv_id, observed 2026-05-13T05:57:22.465379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-13T05:56:36.312877Z digest=sha256:b8eb6844371317ee244b291b452ebbedaa5baac2b1a18b721037923daadbfc7d

Observation 663154c7-579a-476e-af7a-fdc6b2c30fc7 · inbound

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows cites this paper.

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:05:46.759220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T22:18:45.189576Z digest=sha256:68d8d64b4d32eca4cb80ba46c386b287a28417996122fc708ea5cda0ad737cba

Observation a0208dec-ee30-493b-b2bc-9a37eba5b346 · inbound

GEAR: Genetic AutoResearch for Agentic Code Evolution cites this paper.

GEAR: Genetic AutoResearch for Agentic Code Evolution ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:25:07.790561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T06:20:37.051754Z digest=sha256:ae8bbafc929e74ea516d8e6329c46e3fddf6a8e68634289f3f8f4336f9278003

Observation c6ad2a42-525d-48a0-8171-295d1fbe96b2 · inbound

SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research cites this paper.

SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:46:39.348275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-25T05:45:54.275921Z digest=sha256:7ef4e40615f018ad5d2196c36a4f1f4371ab4f515a28c8c61422df2f8609b7c4

Observation a9db3cac-01f8-4579-a4a1-87af99af9cd3 · inbound

AIBuildAI-2: A Knowledge-Enhanced Agent for Automatically Building AI Models cites this paper.

AIBuildAI-2: A Knowledge-Enhanced Agent for Automatically Building AI Models ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-29T12:43:26.073400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T12:33:44.929002Z digest=sha256:6d461645add6ffdd861c904d6b4916331a68e1cb210b662aa7ce58ef381c29c1

Observation 1d176d61-b7b9-4d91-bdee-42b69971b002 · inbound

EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management cites this paper.

EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-02T03:56:35.093530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-28T09:32:51.765633Z digest=sha256:5c8bfd96570e618f7e79c23788b5a1fc11ffbc4e5f16df543e6d87bb5a4a6407

Observation 55bd829c-ef67-43eb-9e79-2013f83eab18 · inbound

MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery cites this paper.

MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:46:59.841297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-28T00:57:02.959467Z digest=sha256:749eb476cd827b52ef2a0a7abfc16c6dbb7d287dac46c25d6529740927fa28e2

Observation 91775afc-beda-41fb-a1b2-cc7928ae5b2e · inbound

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement cites this paper.

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 134

Resolution
metadata mismatch
arxiv_id, observed 2026-06-27T09:40:46.991899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-27T09:34:41.800309Z digest=sha256:314408a647a0b65a27d3568d2a120f8c4a0304c5f3a3ed4b0ec15d0451501407

Observation f59459f5-0d1b-4b13-98a3-e6b04a517952 · inbound

LQCDMaster: Agentic Scientific Computing for Lattice Quantum Chromodynamics Research cites this paper.

LQCDMaster: Agentic Scientific Computing for Lattice Quantum Chromodynamics Research ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-02T00:32:16.368828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:32:16.368828Z digest=sha256:8f5eb7de4aa5fe64f0970f1951cf2c23135453401f3775cad212d0099397672a

Observation 47ed4700-2382-485d-8a6d-862d9e29a233 · inbound

PEARL: Solver-in-the-Loop Interactive Optimization Modeling from Natural Language cites this paper.

PEARL: Solver-in-the-Loop Interactive Optimization Modeling from Natural Language ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-02T14:04:57.232384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T14:04:57.232384Z digest=sha256:c60999321cac9a98d96c0e2548704d14fd5867ef4db0496694af58e2b1f3dcc5

Observation 7c1bfa33-2170-4742-9a48-68f1d1cbd4d7 · inbound

RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems cites this paper.

RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-03T11:00:13.190983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T11:00:13.190983Z digest=sha256:721c579b0cec621b2b9ed978956b1badc47054e8157cd733cfd60dfcdf38e263

Observation 7d61f8e8-1309-4d5e-82cf-a4e83a7e1787 · inbound

Idea Search: Guiding Tree Search with Ideas to Explore Diverse Scientific Methods cites this paper.

Idea Search: Guiding Tree Search with Ideas to Explore Diverse Scientific Methods ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T04:23:27.402281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:23:27.402281Z digest=sha256:df9c9ee6125b8c63ea10d5fe197d543f9df0fe1f456f057adbe3c8ab24fe9d82

Observation 8ba0a8c5-4189-4549-997a-73b4de388fe2 · inbound

Recovering Wasted Compute in Autoresearch Agents cites this paper.

Recovering Wasted Compute in Autoresearch Agents ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T14:26:19.464207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:26:19.464207Z digest=sha256:4b02061ff85141155e1db2fee4905460a930c9745e33a144c288b91db327d1a7

Observation f9c7d4b0-0cb0-4cdb-8878-5417c7c59b5d · inbound

Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence cites this paper.

Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-16T00:25:16.606463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:25:16.606463Z digest=sha256:ff79b0121d7d67f1e4fef7f9f91b19c9c51216354296f2d73f3937deef26723a