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Paper Citation Record · LEDGER

Large Language Models for Mathematical Reasoning: Progresses and Challenges

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 55 inbound Pith citation observations for arXiv:2402.00157.

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

pith.paper-citation-record.v1
2402.00157 v4

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measured 0 of 0 reference resolution

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measured 55 of 55 standing notices

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

measured 55 of 55 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:10:44.347345Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-07-04T11:39:46.423009Z

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Outbound references

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Pith citing papers

Observation f7bee619-0adb-4582-aea6-e6643ed9362a · inbound

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 38

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arxiv_id, observed 2026-05-23T19:45:47.247483Z

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

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Observation 13237bbd-396e-47ce-8b20-4238944258aa · inbound

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection cites this paper.

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

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arxiv_id, observed 2026-05-23T20:13:24.615341Z

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source=arxiv_source observed=2026-05-23T20:10:59.264484Z digest=sha256:0aa145bf299430bb8020b9a99537b9bbf75f17eb0d7485b43214e94b66f5686c

Observation 3aa80304-020b-4b5b-a6fe-8b0a762a150d · inbound

Enhancing LLM Character-Level Manipulation via Divide and Conquer cites this paper.

Enhancing LLM Character-Level Manipulation via Divide and Conquer Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

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Observation c4a713b8-e40b-4c48-a05b-781ed5aeaa3c · inbound

R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization cites this paper.

R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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arxiv_id, observed 2026-05-16T00:19:20.632524Z

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Observation 04501110-030e-4523-9fd0-d0f864796504 · inbound

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems cites this paper.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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arxiv_id, observed 2026-05-22T22:57:13.238711Z

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Observation f8c76616-33a6-4103-8028-772e93c789c0 · inbound

Bridging Language Models and Financial Analysis cites this paper.

Bridging Language Models and Financial Analysis Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

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arxiv_id, observed 2026-05-23T01:12:20.566155Z

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Observation 0626d88e-ff78-485b-872c-82391f719e8b · inbound

MIST: A Co-Design Framework for Heterogeneous, Multi-Stage LLM Inference cites this paper.

MIST: A Co-Design Framework for Heterogeneous, Multi-Stage LLM Inference Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 8

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arxiv_id, observed 2026-05-22T21:17:08.075906Z

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Observation 0debd0e8-2f95-46c1-922f-d2871a15e295 · inbound

Can reasoning models comprehend mathematical problems in Chinese ancient texts? An empirical study based on data from Suanjing Shishu cites this paper.

Can reasoning models comprehend mathematical problems in Chinese ancient texts? An empirical study based on data from Suanjing Shishu Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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Observation e9182548-547a-48f2-9993-f7c7ca9a5b69 · inbound

Towards General Continuous Memory for Vision-Language Models cites this paper.

Towards General Continuous Memory for Vision-Language Models Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

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Observation 11854a30-41ac-4009-8b4a-a13ac9f96c7f · inbound

Sensorimotor Self-Recognition in Multimodal Large Language Model-Driven Robots cites this paper.

Sensorimotor Self-Recognition in Multimodal Large Language Model-Driven Robots Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 14

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arxiv_id, observed 2026-05-19T13:32:19.252896Z

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Observation 34ac6422-b4c4-4d98-8f2d-935ee4a39d94 · inbound

CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesis cites this paper.

CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesis Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

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Observation 86ee1e6a-fce2-49dd-a44a-16f4bd01b9e5 · inbound

Think Again! The Effect of Test-Time Compute on Preferences, Opinions, and Beliefs of Large Language Models cites this paper.

Think Again! The Effect of Test-Time Compute on Preferences, Opinions, and Beliefs of Large Language Models Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

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source=arxiv_source observed=2026-08-07T14:14:40.022995Z digest=sha256:b80ad798cab7e2f1a00dc56240cec60299d1ece92ec9be3b86ca6df3a44b3c35

Observation 2cc13414-55b7-4a9c-abf4-e85bea0b9a3f · inbound

Probability-Consistent Preference Optimization for Enhanced LLM Reasoning cites this paper.

Probability-Consistent Preference Optimization for Enhanced LLM Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

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Observation 6f1d3a81-d2e7-4427-9aac-d007c05be2cc · inbound

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction cites this paper.

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

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arxiv_id, observed 2026-05-19T11:37:15.930637Z

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Observation a381e39a-81c4-4b8d-b03a-f5c4c46c26f0 · inbound

Knowledge or Reasoning? A Close Look at How LLMs Think Across Domains cites this paper.

Knowledge or Reasoning? A Close Look at How LLMs Think Across Domains Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 5

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Observation 74ae6843-d300-4d16-a475-a45ff3ad223e · inbound

Learning to Insert [PAUSE] Tokens for Better Reasoning cites this paper.

Learning to Insert [PAUSE] Tokens for Better Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

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source=arxiv_source observed=2026-08-07T11:06:16.657975Z digest=sha256:002c086446694df84808b727c9a3b7837da949e594c0c25701c4aef4ecae0c30

Observation 2029e78c-c795-4bb7-9a6e-ae7d46f2f301 · inbound

More or Less Wrong: A Benchmark for Directional Bias in LLM Comparative Reasoning cites this paper.

More or Less Wrong: A Benchmark for Directional Bias in LLM Comparative Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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source=arxiv_source observed=2026-08-07T10:59:03.671310Z digest=sha256:ada2c9d9af4c68027efb28a85a74ca12b941b3dda42ce26fe339bc71bdf11478

Observation ecd86cd7-3a10-4636-b632-d0e84df0588b · inbound

Structured Pruning for Diverse Best-of-N Reasoning Optimization cites this paper.

Structured Pruning for Diverse Best-of-N Reasoning Optimization Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

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source=arxiv_source observed=2026-08-07T10:56:23.511738Z digest=sha256:bf17f1fecf7cb6c8c02f5c4804c79abf72c80b0a5d4e4fd1c79ee5b7eb44364b

Observation 0a8b4406-5832-45e1-8897-10e849757da2 · inbound

Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification cites this paper.

Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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Observation be2ce9b2-d613-4dbb-a653-1a88b64c37dc · inbound

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration cites this paper.

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 26

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Observation 24a13888-daca-4c40-a5e3-a013ce5f0b46 · inbound

WIP: Large Language Model-Enhanced Smart Tutor for Undergraduate Circuit Analysis cites this paper.

WIP: Large Language Model-Enhanced Smart Tutor for Undergraduate Circuit Analysis Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 13

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Observation d1d4f725-ebfb-4830-a238-2ba40941af84 · inbound

AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions cites this paper.

AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 11

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Observation d739b67a-0cd2-485d-a83c-f8f98f421293 · inbound

WGSR-Bench: Wargame-based Game-theoretic Strategic Reasoning Benchmark for Large Language Models cites this paper.

WGSR-Bench: Wargame-based Game-theoretic Strategic Reasoning Benchmark for Large Language Models Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 7

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source=pdf_text observed=2026-08-07T04:34:37.342152Z digest=sha256:98c151fd54872a13e0c55737bfc71bde87e8cfb0483c44d15a6d2f40529e96e2

Observation a761afb0-eef9-4f53-bd59-c84dae9dabb1 · 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 Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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source=arxiv_source observed=2026-08-06T23:33:52.072107Z digest=sha256:ffcaec74d675f02e0c11822770023f7be9cfe80aef079df4dc150a4687caae8f

Observation fa880957-aadb-49d0-983f-bc115dddfae6 · inbound

A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis cites this paper.

A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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source=arxiv_source observed=2026-08-06T22:21:09.695912Z digest=sha256:868e77638ef5dcee73dbd65d8b85f8bc090feb1f145dd034039d44ed393a042d

Observation 53abae40-7d72-498a-b040-d722d87eaa46 · inbound

Fine-tuning Large Language Model for Automated Algorithm Design cites this paper.

Fine-tuning Large Language Model for Automated Algorithm Design Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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arxiv_id, observed 2026-05-21T23:40:46.609814Z

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

source=arxiv_source observed=2026-05-21T23:36:12.949230Z digest=sha256:cde4beb30f0c8096c378bee2c94ab4da4499bb7211b7220c3303ba838760ea72

Observation 24462251-b2e1-4f83-9d93-4fbf38474a15 · inbound

Beyond Isolated Capabilities: Bridging Long CoT Reasoning and Long-Context Understanding cites this paper.

Beyond Isolated Capabilities: Bridging Long CoT Reasoning and Long-Context Understanding Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

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no resolver link, observed 2026-08-06T15:50:50.090392Z

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source=arxiv_source observed=2026-08-06T15:50:50.090392Z digest=sha256:a09af7f5a40224ae9a2e76ecaa660daef0e90d401726b8b167151ec2bb72540d

Observation 111c09e7-d199-49e0-b63d-8387169a80df · inbound

League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models cites this paper.

League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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arxiv_id, observed 2026-05-19T03:22:01.377367Z

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source=arxiv_source observed=2026-05-19T03:17:06.457421Z digest=sha256:6490a7fbfdcf44b882c3a3f172227dc18c1a5de8ca3cf3e4623203852b187d5d

Observation 7a9e52fd-f93e-4f87-9c88-d049b7cc2b5e · inbound

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning cites this paper.

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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source=arxiv_source observed=2026-08-06T00:59:51.320079Z digest=sha256:21238814776444408060bf0526d5bdf8a96e25fa55fd24feba550d8540ae6517

Observation 62408393-31d2-47ba-943b-972c66d72903 · inbound

Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness cites this paper.

Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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no resolver link, observed 2026-08-05T16:15:28.188254Z

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source=pdf_text observed=2026-08-05T16:15:28.188254Z digest=sha256:8b15cac030a92dd08e6d884112f980fb29569e47a9dce21a53e37049a2f7e67d

Observation 512aafcd-8ce9-4e71-992d-fd284663d72a · inbound

Do AI Models Dream of Faster Code? An Empirical Study on LLM-Proposed Performance Improvements in Real-World Software cites this paper.

Do AI Models Dream of Faster Code? An Empirical Study on LLM-Proposed Performance Improvements in Real-World Software Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

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arxiv_id, observed 2026-05-18T06:41:00.361974Z

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

source=pdf_text observed=2026-05-18T06:39:42.391102Z digest=sha256:26c6bf4c93b49f252c766b5b0f6d6934cd68d57f1f5325b5a6cea7e7cb71de70

Observation 4c1eaf67-c7ec-418a-9be1-98e3e788253b · inbound

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle cites this paper.

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 40

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arxiv_id, observed 2026-05-18T06:20:58.331885Z

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

source=pdf_text observed=2026-05-18T06:19:44.360734Z digest=sha256:7e39c2f2a7c73b867805cda2f3a706e0724a8ad1eca8d3fe05066f143f32a254

Observation f5e710a1-c167-47cf-a778-f3f460b7ed4f · inbound

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle cites this paper.

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 40

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arxiv_id, observed 2026-05-21T20:50:36.463555Z

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

source=pdf_text observed=2026-05-21T20:50:06.642976Z digest=sha256:10ac7b67fedd1c9707ebab71a642270f7d26ad5ebf1f26890cb7b889f4ea8c89

Observation 5d3077fa-e6e1-4769-a846-722822d633b5 · inbound

ReasonBENCH: Benchmarking the (In)Stability of LLM Reasoning cites this paper.

ReasonBENCH: Benchmarking the (In)Stability of LLM Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2025

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source=pdf_text observed=2026-08-03T17:53:53.227185Z digest=sha256:5a11e8263d7371e7bcaa416e71204cadf85820bd8f15ee13f13e665e31b2feef

Observation 422c3237-8120-4ad2-82f6-a6e0c104d21a · inbound

One Tool Is Enough: Reinforcement Learning for Repository-Level LLM Agents cites this paper.

One Tool Is Enough: Reinforcement Learning for Repository-Level LLM Agents Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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no resolver link, observed 2026-08-03T14:20:31.208360Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:20:31.208360Z digest=sha256:a5a5365e353084bf8d0481ee45230b9ac7975a26ea5d14b301aea0872ffa0573

Observation d299b128-0f29-4165-b051-41baea0c6acf · inbound

From Meta-Thought to Execution: Cognitively Aligned Post-Training for Generalizable and Reliable LLM Reasoning cites this paper.

From Meta-Thought to Execution: Cognitively Aligned Post-Training for Generalizable and Reliable LLM Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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no resolver link, observed 2026-08-03T06:52:52.486546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T06:52:52.486546Z digest=sha256:3a3717ae5c58f815ef61b69cbf6951dee565e021eb5e43a2fce4989fb023f768

Observation e830e4be-7dd7-4964-a2eb-92129905252c · inbound

Adaptive Information Control for Search-Augmented LLM Reasoning cites this paper.

Adaptive Information Control for Search-Augmented LLM Reasoning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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no resolver link, observed 2026-08-03T05:39:26.664534Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:39:26.664534Z digest=sha256:374c3299ffc4ab070bdab40478c7d9ed6a49f99f1fa3b403327c795f6fe09858

Observation 334648bc-16d3-4fe1-8a89-be89d1d21707 · inbound

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing cites this paper.

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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verified exact
arxiv_id, observed 2026-05-16T08:17:36.698867Z

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.

source=pdf_text observed=2026-05-16T08:12:55.296932Z digest=sha256:481f5ef21ce1224dc0d4fe5fdfedbaabcb850e75ce70b045a0a60b395287c6ba

Observation 7f0e494e-5058-4140-a1f9-5b67215432df · inbound

Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals cites this paper.

Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T05:16:27.580989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:16:27.580989Z digest=sha256:15a3a55056074f19783730b664cdf913c28d678533b50828d23466a495309478

Observation 7e3a12e5-a8f9-42fa-876c-a72a0125441f · inbound

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving cites this paper.

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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verified exact
arxiv_id, observed 2026-05-11T21:11:16.038853Z

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.

source=pdf_text observed=2026-05-08T06:33:29.860024Z digest=sha256:c5295e256cd743fa19497b4a089a728b1504c47107417f2a9f79628a015907a2

Observation c949b87c-15f4-489d-a476-0f37a94bcc5f · inbound

Improving Medical VQA through Trajectory-Aware Process Supervision cites this paper.

Improving Medical VQA through Trajectory-Aware Process Supervision Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:06:06.836267Z

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.

source=pdf_text observed=2026-05-10T17:18:17.846140Z digest=sha256:f9421038fba4c0b661e20fa963eec4ae7c90271ce89719987b0b0de72a3e8194

Observation d33476eb-029c-42a1-893c-bc56de0cd37b · inbound

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning cites this paper.

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:06:33.167115Z

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.

source=pdf_text observed=2026-05-12T03:45:06.199636Z digest=sha256:295654f38a6e60fd5ccb4276140cee702cf2ba3202795a07c800dbd0a1f2ba8c

Observation 37686144-eed6-4c86-87a8-55572a54d23d · inbound

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning cites this paper.

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:23:48.380113Z

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.

source=pdf_text observed=2026-05-20T22:19:49.016156Z digest=sha256:c3ac15351ecdbb27aaa0bbf3ad9be31a75d1ce237bb04e8ba79835e98cf4723e

Observation f3f1dc8c-8d96-48bb-9328-57bff04c810e · inbound

CLORE: Content-Level Optimization for Reasoning Efficiency cites this paper.

CLORE: Content-Level Optimization for Reasoning Efficiency Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-22T05:51:08.336753Z

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.

source=pdf_text observed=2026-05-22T05:50:23.111591Z digest=sha256:838589e4b5cf75cf0858f07804ca820538fe870258258a327420f7acfdd38733

Observation c32279f1-64e2-4c06-b8d5-b7cf6048a143 · inbound

Inferring Code Correctness from Specification cites this paper.

Inferring Code Correctness from Specification Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:33:31.522748Z

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.

source=pdf_text observed=2026-06-29T06:33:36.835860Z digest=sha256:f82dff82e2f43c7f7ce9d575c2b832ecd7ce71280c73e45ee7eb4bba3161c226

Observation 3471314e-5241-41d6-a401-14001a03eb74 · inbound

LLM Parameters for Math Across Languages: Shared or Separate? cites this paper.

LLM Parameters for Math Across Languages: Shared or Separate? Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T21:28:59.014009Z

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.

source=arxiv_source observed=2026-06-27T00:30:30.315423Z digest=sha256:0cf2885796a62cdd052070f5e0a563f8e287659cc868e9761ecf917110a223d3

Observation 87d19f32-075e-41c3-ba18-fe4ca06fb773 · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 244

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T11:39:46.424583Z

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.

source=arxiv_source observed=2026-06-26T07:53:57.250401Z digest=sha256:d0e96b9b2da6ca8dd465f2adeee64a084a17c12c036da542bf2f683275a6fb28

Observation b2e94b4c-eda2-4d4c-9d40-96e85ea54390 · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 248

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T10:14:36.053955Z

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.

source=arxiv_source observed=2026-06-30T10:13:09.503522Z digest=sha256:e819f7fc31a0e9af4ac8ca1e3504227aabb43499ac901a8daa8e1de986d7f199

Observation 41734c81-27c9-49d2-87d2-1667ebe3f3bb · inbound

RareDxR1: Autonomous Medical Reasoning for Rare Disease Diagnosis Beyond Human Annotation cites this paper.

RareDxR1: Autonomous Medical Reasoning for Rare Disease Diagnosis Beyond Human Annotation Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:27:18.591729Z

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.

source=pdf_text observed=2026-07-02T19:21:44.653877Z digest=sha256:ff9df477250595fc961e5622d8279fc57c4c98061182603af9776887ef80fd70

Observation 1b116a76-8459-4a3c-9886-750be77e14ef · inbound

SCAPE: Accurate and Efficient LLM Training with Extreme Sparse Communication cites this paper.

SCAPE: Accurate and Efficient LLM Training with Extreme Sparse Communication Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:58:46.648992Z

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.

source=pdf_text observed=2026-07-03T17:56:52.510949Z digest=sha256:7f881c238f28b046bc341cc9dd87a77378632e5e39fb072ae8a1a231d8e149a9

Observation 57ed5482-221d-49bf-8944-8629815e0a52 · inbound

STEC: Evidence Compression for Deep Search in Open-domain Multi-Hop QA cites this paper.

STEC: Evidence Compression for Deep Search in Open-domain Multi-Hop QA Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 29

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no resolver link, observed 2026-07-14T09:13:24.763990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T09:13:24.763990Z digest=sha256:7ce2c57d61da04c8fc42aecd1cbd17454a8729aeb4254b78bd25f7ac1e65045a

Observation bf9c8779-e9c0-498a-b366-13b4c4e7c92b · inbound

Feature Generation Using LLMs: An Evolutionary Algorithm Approach cites this paper.

Feature Generation Using LLMs: An Evolutionary Algorithm Approach Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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no resolver link, observed 2026-08-02T09:47:29.204988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:47:29.204988Z digest=sha256:04ea232ad0e3d4d13ee4fa9fe3ffc67ec9e89156e92d9989f173fc735ede79a2

Observation 3412a780-27cc-4607-a29d-79e7642dda2a · inbound

Representation Robustness Under Executable Reasoning Constraints in Large Language Models for Mathematical Problem Solving cites this paper.

Representation Robustness Under Executable Reasoning Constraints in Large Language Models for Mathematical Problem Solving Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2

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unresolved
no resolver link, observed 2026-08-02T08:02:56.456065Z

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source=pdf_text observed=2026-08-02T08:02:56.456065Z digest=sha256:21d1d9aaf3153e9ddc102358956e22b5113c890c388a63cfd8afacd6789b55ea

Observation 97a5f922-c734-4b23-81aa-f36ddadd01c2 · inbound

Assessing the Benefits of Combining Advanced Deep Learning Techniques for Post-Disaster Building Damage Assessment from UAV Imagery cites this paper.

Assessing the Benefits of Combining Advanced Deep Learning Techniques for Post-Disaster Building Damage Assessment from UAV Imagery Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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no resolver link, observed 2026-08-04T18:33:54.681432Z

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source=pdf_text observed=2026-08-04T18:33:54.681432Z digest=sha256:c8dc0f766a17a798ec14e3ce46bb9211e596560c4da98c215241decb111e86d0

Observation 48d54ee0-29f6-4edc-8a3a-0ff5dfb28b6c · inbound

Superloop Equations and Minimal Surfaces I: Confining minimal surface in $4D, N=1$ SYM cites this paper.

Superloop Equations and Minimal Surfaces I: Confining minimal surface in $4D, N=1$ SYM Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 277

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no resolver link, observed 2026-08-04T10:28:20.864753Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:28:20.864753Z digest=sha256:9d179525e6e9a1f7e54c75e1cce6b3379e19c31425edc3f296570ff95b6c7e36