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Paper Citation Record · LEDGER

On Memorization of Large Language Models in Logical Reasoning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2410.23123.

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

pith.paper-citation-record.v1
2410.23123 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:54:13.323025Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 94693846-9b8f-46d9-9a5d-ad8a37b73d53 · inbound

Neuron-Level Differentiation of Memorization and Generalization in Large Language Models cites this paper.

Neuron-Level Differentiation of Memorization and Generalization in Large Language Models On Memorization of Large Language Models in Logical Reasoning

Reference 28

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no resolver link, observed 2026-08-11T04:46:40.259044Z

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source=arxiv_source observed=2026-08-11T04:46:40.259044Z digest=sha256:e49db76527b11dbf95717a6fc72d172705da48278ebcd21d9bf9832e39aa4328

Observation 7d89b2f6-5e28-41c5-9f23-4ab67366c90e · inbound

Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards cites this paper.

Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards On Memorization of Large Language Models in Logical Reasoning

Reference 21

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source=pdf_text observed=2026-08-10T20:44:33.029741Z digest=sha256:4c1614aa82e425a43d1572aa056bf2cbb98080bc6f2056ff7a5c90e0d901891d

Observation 042a42bd-9a30-4b46-9e8a-0afdedc4ccdb · inbound

Skewed Memorization in Large Language Models: Quantification and Decomposition cites this paper.

Skewed Memorization in Large Language Models: Quantification and Decomposition On Memorization of Large Language Models in Logical Reasoning

Reference 18

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no resolver link, observed 2026-08-09T16:24:37.539995Z

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source=arxiv_source observed=2026-08-09T16:24:37.539995Z digest=sha256:e515e51866c884930a3ba1d84e4960b9cd2a29a62e528d353f55bf82b6fd800c

Observation 955d6ebd-ebeb-452b-8757-2f1384cde40a · inbound

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations cites this paper.

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations On Memorization of Large Language Models in Logical Reasoning

Reference 26

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no resolver link, observed 2026-08-08T15:26:07.793476Z

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source=pdf_text observed=2026-08-08T15:26:07.793476Z digest=sha256:c9ff9147c78b42380750cf205821228be4c33977e575a637a4e12c18d8edf3c0

Observation 1de13a09-f027-42d6-acd0-36a437ec335b · inbound

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data cites this paper.

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data On Memorization of Large Language Models in Logical Reasoning

Reference 42

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no resolver link, observed 2026-08-16T11:54:13.323025Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:54:13.323025Z digest=sha256:29c2c30a1e5ebb7934f4eac2520903ef43ed69b2a9d3872884b2f8da0ea13e7d

Observation 54eb96ce-458e-4cd7-a0ea-4b0af235d799 · inbound

OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models cites this paper.

OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models On Memorization of Large Language Models in Logical Reasoning

Reference 59

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no resolver link, observed 2026-08-15T23:34:09.910710Z

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source=arxiv_source observed=2026-08-15T23:34:09.910710Z digest=sha256:957b6577541e1d2628b805d40eb9ec93a90d82d6f995c4a479495beb895da012

Observation 778f7272-2792-4308-8ac7-820d26be5555 · inbound

Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs cites this paper.

Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs On Memorization of Large Language Models in Logical Reasoning

Reference 45

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source=pdf_text observed=2026-08-15T20:29:01.697399Z digest=sha256:da4d734447567af01f7ed8ca6e73e69763d7c64922475c5c902be46cccec972e

Observation 5da45bce-06cc-4ac2-8606-f79c7cd96b13 · inbound

DGRO: Enhancing LLM Reasoning via Exploration-Exploitation Control and Reward Variance Management cites this paper.

DGRO: Enhancing LLM Reasoning via Exploration-Exploitation Control and Reward Variance Management On Memorization of Large Language Models in Logical Reasoning

Reference 35

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source=pdf_text observed=2026-08-15T20:31:20.393071Z digest=sha256:1eba7f2985b748c7f091221733729b9ab5903dc9160b778837b1caf474a0bf66

Observation 18575e88-56ee-489f-9617-fde83ef0a83a · inbound

Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning cites this paper.

Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning On Memorization of Large Language Models in Logical Reasoning

Reference 31

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no resolver link, observed 2026-08-07T14:41:42.174397Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:41:42.174397Z digest=sha256:28ef8027132ee2ae0c687ab1129fb2ac071bdfa6c68c963b36f8202878c6af87

Observation 5f47fcea-3355-4ffe-80ab-e14009f0743b · inbound

SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond cites this paper.

SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond On Memorization of Large Language Models in Logical Reasoning

Reference 2022

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no resolver link, observed 2026-08-07T14:14:33.306474Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:33.306474Z digest=sha256:a868e8160d1318d859185b7fb50f01cb87a227b5dce0f9406423fadf0631be9a

Observation 07a88a96-8c18-4647-a1da-a500212b9a05 · inbound

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants cites this paper.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants On Memorization of Large Language Models in Logical Reasoning

Reference 43

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no resolver link, observed 2026-08-07T14:12:38.271159Z

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source=pdf_text observed=2026-08-07T14:12:38.271159Z digest=sha256:b782cad71b95b69e0649654b26e1f1601c0649eaff3ec13e6940f2e5b492333f

Observation ac77cf32-3735-4085-b812-f2775d428793 · inbound

SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis cites this paper.

SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis On Memorization of Large Language Models in Logical Reasoning

Reference 77

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source=pdf_text observed=2026-08-07T13:55:20.193631Z digest=sha256:37fdef29c203c548d2802ed7c901f2207cf1cf4499b63163d6f6c60f74e1d926

Observation 8971f75e-77ab-4780-8d59-2d75b01c8113 · inbound

OIBench: Benchmarking Strong Reasoning Models with Olympiad in Informatics cites this paper.

OIBench: Benchmarking Strong Reasoning Models with Olympiad in Informatics On Memorization of Large Language Models in Logical Reasoning

Reference 4

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source=pdf_text observed=2026-08-07T04:33:08.113023Z digest=sha256:5423f06d2118a9ab1c74fefa676f90d1ce7c71dbe5797c17fa617ae41e69b0ae

Observation 859adbfc-4081-4634-b0af-f5476165a60f · inbound

Beyond Frequency: The Role of Redundancy in Large Language Model Memorization cites this paper.

Beyond Frequency: The Role of Redundancy in Large Language Model Memorization On Memorization of Large Language Models in Logical Reasoning

Reference 11

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source=pdf_text observed=2026-08-07T00:57:29.310664Z digest=sha256:ad51c72648f0b8ed1c3f42270dd4483f09f2fc7274ca84738deecbb48926a75f

Observation 2c51cf2d-7dca-4da1-8cce-8cf34657a295 · inbound

Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs cites this paper.

Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs On Memorization of Large Language Models in Logical Reasoning

Reference 44

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no resolver link, observed 2026-08-06T23:33:56.667467Z

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source=arxiv_source observed=2026-08-06T23:33:56.667467Z digest=sha256:fbda8b65bd345e5701c14bce3d97e6054b476797a84a26ea9fdb8724b8a0fd8a

Observation 5058069b-c939-46af-9846-4f54c05fc867 · inbound

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models cites this paper.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models On Memorization of Large Language Models in Logical Reasoning

Reference 30

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no resolver link, observed 2026-08-06T22:01:23.782702Z

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source=pdf_text observed=2026-08-06T22:01:23.782702Z digest=sha256:c5fbb88378bc00609ed8f3601e5f04f168e96f5bafaddf505b26619f4f6d2d4a

Observation 80371bb5-c4ca-46e4-bbf0-e475c9156cdd · inbound

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling cites this paper.

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling On Memorization of Large Language Models in Logical Reasoning

Reference 40

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arxiv_id, observed 2026-05-21T23:40:46.183831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-21T23:39:39.018498Z digest=sha256:e50fecad1bd7d07df93c4ad8974c9f63b21fab82b4b9435385fd998f0e918fd3

Observation c671e83f-dfbe-4f54-879e-20e84ffe51d9 · inbound

ABench-Physics: Benchmarking Physical Reasoning in LLMs via High-Difficulty and Dynamic Physics Problems cites this paper.

ABench-Physics: Benchmarking Physical Reasoning in LLMs via High-Difficulty and Dynamic Physics Problems On Memorization of Large Language Models in Logical Reasoning

Reference 14

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source=pdf_text observed=2026-08-06T19:46:47.076281Z digest=sha256:aebc4038a61576aece9d8b0c3e817a1bc6090fe82c09215a5b270b0e505a489d

Observation d773d001-007a-45e6-8ad1-31ac21e17281 · inbound

Adaptive Multi-Agent Reasoning via Automated Workflow Generation cites this paper.

Adaptive Multi-Agent Reasoning via Automated Workflow Generation On Memorization of Large Language Models in Logical Reasoning

Reference 7

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source=pdf_text observed=2026-08-06T16:10:28.371589Z digest=sha256:46c739edded1875ebb63b59df97024f5178fbf296b1fe7224b18c381ff795827

Observation 6d631812-2c58-4900-962d-551e04168dad · inbound

Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning cites this paper.

Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning On Memorization of Large Language Models in Logical Reasoning

Reference 37

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source=pdf_text observed=2026-08-06T14:53:04.617685Z digest=sha256:25f4ac97c440143382aee7580638974479b22962c9b09154eab4d68cdbae4753

Observation 6ecbf777-1b7d-48bb-82ab-18fb2e9387f1 · inbound

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends cites this paper.

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends On Memorization of Large Language Models in Logical Reasoning

Reference 154

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arxiv_id, observed 2026-05-18T22:46:53.088164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T22:45:31.935618Z digest=sha256:4f79669ecbe8983189a665000fde1b3bb22191403d2f8c5f617196789ceb183a

Observation 2f0d4916-daa3-44b0-9fb1-a46938fee10c · inbound

Proximal Supervised Fine-Tuning cites this paper.

Proximal Supervised Fine-Tuning On Memorization of Large Language Models in Logical Reasoning

Reference 25

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arxiv_id, observed 2026-05-18T20:42:50.963306Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T20:42:14.423836Z digest=sha256:72b36fa96714144f1b6bf62cf5f9117efc760e8d25466bce8f0d03ae3a98d19c

Observation 86a728e8-2a8a-4654-a142-3bf60067f19a · inbound

Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs cites this paper.

Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs On Memorization of Large Language Models in Logical Reasoning

Reference 38

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arxiv_id, observed 2026-05-18T21:16:50.958282Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-18T21:16:15.703057Z digest=sha256:8371061c9c7bfac8add2bbfcb0b20850d583eb3a00eedc8da3fde41591a0c1c5

Observation 68f50198-fd12-4fc4-aab7-755095cc9c30 · inbound

Throttling Web Agents Using Reasoning Gates cites this paper.

Throttling Web Agents Using Reasoning Gates On Memorization of Large Language Models in Logical Reasoning

Reference 100

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source=pdf_text observed=2026-08-05T12:28:04.901907Z digest=sha256:0a4550bab4bf897bb68aab406b4fa5d4de4bd5a260578cb77e8c06a9e893854b

Observation 826873e2-d18e-4908-86d7-dabbfa8d94fb · inbound

Structured In-context Environment Scaling for Large Language Model Reasoning cites this paper.

Structured In-context Environment Scaling for Large Language Model Reasoning On Memorization of Large Language Models in Logical Reasoning

Reference 24

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arxiv_id, observed 2026-05-18T12:26:22.448289Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T12:23:15.257737Z digest=sha256:16519465ee730d029123759bdba69f2c9e30dd536c67ab292eca356f507097c1

Observation e300f7dd-ab3a-47ad-86de-3bea83be26c2 · inbound

Understanding the Ability of LLMs to Handle Character-Level Perturbation cites this paper.

Understanding the Ability of LLMs to Handle Character-Level Perturbation On Memorization of Large Language Models in Logical Reasoning

Reference 13

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source=pdf_text observed=2026-08-04T09:39:02.711902Z digest=sha256:667deeb875115f4c3886f262958ae15badff5629334da003a4f7ec54e403c632

Observation 978e29cc-951a-4a04-ae3e-1a31a4b8c99b · inbound

ActivationReasoning: Logical Reasoning in Latent Activation Spaces cites this paper.

ActivationReasoning: Logical Reasoning in Latent Activation Spaces On Memorization of Large Language Models in Logical Reasoning

Reference 20

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arxiv_id, observed 2026-05-18T05:45:56.253320Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T05:43:45.863209Z digest=sha256:7f7659217161b327d7cac0ea3b7a9e8f4fc82810f8ba6bf6c3db7039552cd390

Observation b2cfbee7-703a-4d7b-8ae5-f9932440e2bf · inbound

Sharpness-Guided Group Relative Policy Optimization via Probability Shaping cites this paper.

Sharpness-Guided Group Relative Policy Optimization via Probability Shaping On Memorization of Large Language Models in Logical Reasoning

Reference 36

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arxiv_id, observed 2026-05-18T03:12:22.384195Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T03:10:57.839146Z digest=sha256:64825aef714f6491be10ad6c62b02b1e7f9ab71fc96f2aa49b4834c5290c659e

Observation e2b3afbe-65f8-42f1-941a-0635d7f30ff1 · inbound

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments cites this paper.

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments On Memorization of Large Language Models in Logical Reasoning

Reference 56

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source=arxiv_source observed=2026-08-03T23:08:09.608509Z digest=sha256:945bf5b300d93388b5071b6d9f092a206ac7ba125fe622470a144e58a8fd0731

Observation 4558a426-b962-486f-b5e6-d3633d0938b4 · inbound

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering cites this paper.

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering On Memorization of Large Language Models in Logical Reasoning

Reference 40

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arxiv_id, observed 2026-05-11T13:51:04.598671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-09T23:56:42.453216Z digest=sha256:bc914129f39790b8381e7e65f4d98aea82acb4310e86fa30e16152a15bd79170

Observation 06396d8a-df58-4307-afca-93fc6e979c8c · inbound

Unsteady Metrics and Benchmarking Cultures of AI Model Builders cites this paper.

Unsteady Metrics and Benchmarking Cultures of AI Model Builders On Memorization of Large Language Models in Logical Reasoning

Reference 64

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verified exact
arxiv_id, observed 2026-05-15T04:55:03.306773Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T04:54:26.888562Z digest=sha256:c3e00aa78aa7de05680ff9356705e8a67117577e4759d582c10bb2d5087b0a0b

Observation ef3bd5f2-83b4-47bb-9831-22f4c37cfd19 · inbound

Entropy-KL Divergence-based Token Masking: A Novel Approach for Selective Fine-tuning of Large Language Models cites this paper.

Entropy-KL Divergence-based Token Masking: A Novel Approach for Selective Fine-tuning of Large Language Models On Memorization of Large Language Models in Logical Reasoning

Reference 35

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arxiv_id, observed 2026-06-29T08:03:13.507007Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-29T08:01:39.412431Z digest=sha256:f485563e5870322d018112e588f966cc8c6a399f1729c5f46f50f979f8047081

Observation 205eac9a-7f3f-473f-9b7e-ba3b271e323d · inbound

On the Generalization Gap in Self-Evolving Language Model Reasoning cites this paper.

On the Generalization Gap in Self-Evolving Language Model Reasoning On Memorization of Large Language Models in Logical Reasoning

Reference 39

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verified exact
arxiv_id, observed 2026-06-28T17:22:24.888547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T17:18:37.671369Z digest=sha256:a1cd3c85e9ff26a912e72f482e13ad15a64daad5e7e79787eb578a4f08df2509

Observation 6abd965e-3715-46e6-b5b7-3a12478a4cc7 · inbound

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners cites this paper.

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners On Memorization of Large Language Models in Logical Reasoning

Reference 26

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verified exact
arxiv_id, observed 2026-07-02T01:46:26.441956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T11:36:14.896698Z digest=sha256:52aa777b7a6bf485fdfff71815a45045abe6337e196de6ebf624ff584a02e08c

Observation a6e792da-d85f-4ec4-a1e1-f9b8abf76e23 · inbound

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs cites this paper.

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs On Memorization of Large Language Models in Logical Reasoning

Reference 51

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no resolver link, observed 2026-08-01T06:05:55.977186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:05:55.977186Z digest=sha256:d75a6a754832ba4adcee3c7f21211ba969beed39c80f168df08a1168f98e799e