Paper Citation Record · LEDGER

Can Past Experience Accelerate LLM Reasoning?

As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2505.20643.

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

pith.paper-citation-record.v1
2505.20643 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:53:59.231906Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy2
unresolved45
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e79aa794-4e35-4392-a350-6b02571a7a8e · outbound

This paper cites GPT-4 Technical Report.

Can Past Experience Accelerate LLM Reasoning? GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.010369Z

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Observation 65ff566f-2321-4744-9e42-1c66abb55d86 · outbound

This paper cites Near-duplicate question detection.

Can Past Experience Accelerate LLM Reasoning? Near-duplicate question detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:54:00.838170Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1e361abd-1865-4666-8d4c-6960c0b93880 · outbound

This paper cites Editing Factual Knowledge in Language Models.

Can Past Experience Accelerate LLM Reasoning? Editing Factual Knowledge in Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.692399Z

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Observation e4bff9ed-02ec-4ea1-8fc9-246b38f280d0 · outbound

This paper cites AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models.

Can Past Experience Accelerate LLM Reasoning? AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.857065Z

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Observation db427559-1d5c-4206-92ed-026d48eec8af · outbound

This paper cites Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training.

Can Past Experience Accelerate LLM Reasoning? Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.952185Z

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Observation bbac63fc-c4f5-4ebc-a82e-05ac9a54ebd9 · outbound

This paper cites CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.

Can Past Experience Accelerate LLM Reasoning? CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.052600Z

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Observation 1216ef42-4154-4d8a-b68e-e40f0f23babc · outbound

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

Can Past Experience Accelerate LLM Reasoning? rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.145963Z

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Observation 5f028e76-2d78-47c7-87e5-ed889179c166 · outbound

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

Can Past Experience Accelerate LLM Reasoning? DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.228651Z

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Observation 483f4a1e-f312-4f72-9254-651d226aa27c · outbound

This paper cites Token-Budget-Aware LLM Reasoning.

Can Past Experience Accelerate LLM Reasoning? Token-Budget-Aware LLM Reasoning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.318910Z

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Observation a6b89bf5-751a-47d8-9a99-62b9f5abda79 · outbound

This paper cites Training Large Language Models to Reason in a Continuous Latent Space.

Can Past Experience Accelerate LLM Reasoning? Training Large Language Models to Reason in a Continuous Latent Space

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.411702Z

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Observation 481d30a5-c841-4a7c-8ea4-0309164542d0 · outbound

This paper cites ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory.

Can Past Experience Accelerate LLM Reasoning? ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.509501Z

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Observation 190ce8af-065a-4b54-9395-41eff6c02270 · outbound

This paper cites OpenAI o1 System Card.

Can Past Experience Accelerate LLM Reasoning? OpenAI o1 System Card

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.693894Z

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Observation bc71b582-9553-4a5d-9fae-ab5a1af54ad4 · outbound

This paper cites A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning.

Can Past Experience Accelerate LLM Reasoning? A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.789043Z

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Observation 403a5b76-5ee4-4c61-a5f3-96edc1b40eb2 · outbound

This paper cites How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach.

Can Past Experience Accelerate LLM Reasoning? How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.890817Z

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Observation 92678161-cada-44f8-9df8-7165bec7b729 · outbound

This paper cites How long can context length of open-source llms truly promise? InNeurIPS 2023 Workshop on Instruction Tuning and Instruction Following,.

Can Past Experience Accelerate LLM Reasoning? How long can context length of open-source llms truly promise? InNeurIPS 2023 Workshop on Instruction Tuning and Instruction Following,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:54:00.614905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41f5bf51-2a7d-4928-bb29-659d5e9e4d8c · outbound

This paper cites GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models.

Can Past Experience Accelerate LLM Reasoning? GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.066714Z

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Unavailable: canonical work link unavailable.

Observation 3c6dc0ce-f9df-42dc-af0f-393301a3ba99 · outbound

This paper cites From System 1 to System 2: A Survey of Reasoning Large Language Models.

Can Past Experience Accelerate LLM Reasoning? From System 1 to System 2: A Survey of Reasoning Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.137704Z

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Observation 01720339-1bdc-4556-b785-4f68c4ac6eb1 · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

Can Past Experience Accelerate LLM Reasoning? Lost in the Middle: How Language Models Use Long Contexts

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.209320Z

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Observation c08a3bb2-51a6-464e-bd4b-23b5a2357fc3 · outbound

This paper cites Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling.

Can Past Experience Accelerate LLM Reasoning? Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.290694Z

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Observation 8c49f7fd-9a84-4aa2-850a-a0dcda3dc45e · outbound

This paper cites An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning.

Can Past Experience Accelerate LLM Reasoning? An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.428704Z

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Observation 55fbb7ce-d022-45f1-8e90-a4e0ac86edf3 · outbound

This paper cites Fast Model Editing at Scale.

Can Past Experience Accelerate LLM Reasoning? Fast Model Editing at Scale

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.519013Z

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Unavailable: canonical work link unavailable.

Observation 844595f0-86a4-4edd-856f-3eefa4587210 · outbound

This paper cites s1: Simple test-time scaling.

Can Past Experience Accelerate LLM Reasoning? s1: Simple test-time scaling

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.585308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9606b1ba-afb5-415c-818d-f2e611fb28dd · outbound

This paper cites Self-Training Elicits Concise Reasoning in Large Language Models.

Can Past Experience Accelerate LLM Reasoning? Self-Training Elicits Concise Reasoning in Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.717067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31782a33-d74e-4356-aa41-cca451875cec · outbound

This paper cites Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights.

Can Past Experience Accelerate LLM Reasoning? Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.803026Z

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Observation effb7cc5-a379-4d1f-8e80-e2cb6d5dc74d · outbound

This paper cites Self-Reflection in LLM Agents: Effects on Problem-Solving Performance.

Can Past Experience Accelerate LLM Reasoning? Self-Reflection in LLM Agents: Effects on Problem-Solving Performance

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.901289Z

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Observation dd31b16e-7ba3-47d7-a301-90e290e04293 · outbound

This paper cites Character-LLM: A Trainable Agent for Role-Playing.

Can Past Experience Accelerate LLM Reasoning? Character-LLM: A Trainable Agent for Role-Playing

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.972825Z

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Observation 144b36bc-e197-4181-a33d-f506da3a6667 · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Can Past Experience Accelerate LLM Reasoning? Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.056976Z

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Observation f3eff320-a979-4fb8-88dc-f7affa2d6392 · outbound

This paper cites Fast Best-of-N Decoding via Speculative Rejection.

Can Past Experience Accelerate LLM Reasoning? Fast Best-of-N Decoding via Speculative Rejection

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.149803Z

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Observation 15e10d43-6b50-445b-9d0b-b66d1baecc23 · outbound

This paper cites TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation.

Can Past Experience Accelerate LLM Reasoning? TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.239786Z

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Observation 50c9288d-24a2-40a5-9ee2-689ce230da04 · outbound

This paper cites Online Adaptation of Language Models with a Memory of Amortized Contexts.

Can Past Experience Accelerate LLM Reasoning? Online Adaptation of Language Models with a Memory of Amortized Contexts

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.345733Z

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Observation 196d8e17-83c5-413d-b60e-a07ac73b67fd · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Can Past Experience Accelerate LLM Reasoning? Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.464435Z

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Observation 689bb24c-34cb-4fa2-91fe-82f06f25cdcc · outbound

This paper cites SCM: Enhancing Large Language Model with Self-Controlled Memory Framework.

Can Past Experience Accelerate LLM Reasoning? SCM: Enhancing Large Language Model with Self-Controlled Memory Framework

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.558935Z

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Observation a1caa4ea-230f-408c-9ad8-64f4a7ba1db8 · outbound

This paper cites Sampling-efficient test-time scaling: Self-estimating the best-of-n sampling in early decoding.arXiv preprint arXiv:2503.01422,.

Can Past Experience Accelerate LLM Reasoning? Sampling-efficient test-time scaling: Self-estimating the best-of-n sampling in early decoding.arXiv preprint arXiv:2503.01422,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.690570Z

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Observation 992584c7-4850-4257-aac8-28332c9690cf · outbound

This paper cites Chain of Draft: Thinking Faster by Writing Less.

Can Past Experience Accelerate LLM Reasoning? Chain of Draft: Thinking Faster by Writing Less

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.756755Z

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Observation ed294341-ec12-4716-b109-3a4550ce41d3 · outbound

This paper cites LIMO: Less is More for Reasoning.

Can Past Experience Accelerate LLM Reasoning? LIMO: Less is More for Reasoning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.863328Z

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Observation bf20a9b4-4ebd-49ae-bc8d-e2f8199f9575 · outbound

This paper cites Deeper Insights Without Updates: The Power of In-Context Learning Over Fine-Tuning.

Can Past Experience Accelerate LLM Reasoning? Deeper Insights Without Updates: The Power of In-Context Learning Over Fine-Tuning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:58.992261Z

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Observation 082e6222-e12c-43cd-bd40-65da9f69ca12 · outbound

This paper cites On the Structural Memory of LLM Agents.

Can Past Experience Accelerate LLM Reasoning? On the Structural Memory of LLM Agents

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:59.079201Z

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Observation eb936d18-b3e8-45db-b6e0-b3f147d79c15 · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

Can Past Experience Accelerate LLM Reasoning? When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:59.151322Z

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Observation fec81309-e0f3-4b9f-9126-c75617c93263 · outbound

This paper cites Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control.

Can Past Experience Accelerate LLM Reasoning? Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:59.231906Z

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Observation 9d694ca8-4b0c-4b65-93cf-9384812c92fd · outbound

This paper cites AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents.

Can Past Experience Accelerate LLM Reasoning? AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents

Reference 1982

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.194944Z

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Observation 8239878e-cccd-480f-8f3f-cdb8a8cdf616 · outbound

This paper cites O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning.

Can Past Experience Accelerate LLM Reasoning? O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning

Reference 1988

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:57.355274Z

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Observation f8fef601-be25-411f-95b7-d37a102b3197 · outbound

This paper cites Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models.

Can Past Experience Accelerate LLM Reasoning? Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.389279Z

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Observation b77cf157-2608-437d-b359-00e3add75c2f · outbound

This paper cites Dynamic Parallel Tree Search for Efficient LLM Reasoning.

Can Past Experience Accelerate LLM Reasoning? Dynamic Parallel Tree Search for Efficient LLM Reasoning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.776430Z

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Observation 3142b187-2d3b-4d93-813f-ddf27c932d0a · outbound

This paper cites Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations.

Can Past Experience Accelerate LLM Reasoning? Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:56.601207Z

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Observation 6b3574d1-32ad-4544-a2f5-e625828add17 · outbound

This paper cites L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning.

Can Past Experience Accelerate LLM Reasoning? L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.101105Z

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Observation fa2aaab7-a351-4a90-9081-218a2866ca63 · outbound

This paper cites Language models are few-shot learners.

Can Past Experience Accelerate LLM Reasoning? Language models are few-shot learners

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.269334Z

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Observation 307cd9db-5382-4e6d-b28e-a91f47090434 · outbound

This paper cites Compressed Chain of Thought: Efficient Reasoning Through Dense Representations.

Can Past Experience Accelerate LLM Reasoning? Compressed Chain of Thought: Efficient Reasoning Through Dense Representations

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:55.493682Z

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Pith citing papers

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