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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 54 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 54 of 54 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 54 of 54 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:01:05.646723Z

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 2026-08-07T06:34:17.273281+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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-23T20:10:59.264484Z digest=sha256:098becb49cd2562da04c98d2b3e704222d7db2eeb6752372eb8303411e7cd5cd

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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T22:55:34.238427Z digest=sha256:0cbe757e39a6fc3f1c4a1bad1946054fe594d95d2589c1dac52c68c63ae223c8

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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source=pdf_text observed=2026-05-22T21:16:31.655330Z digest=sha256:4765f12d61d3d207cb805d5ad51e0ccf8e2c0a1c263a4227e66e3ac4961a11bc

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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source=pdf_text observed=2026-08-07T15:01:05.646723Z digest=sha256:6d506dbc801c60a2f8ae2e9015176d972a9442254a1fc2d7f23761675fd81968

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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source=arxiv_source observed=2026-08-07T14:17:26.062156Z digest=sha256:d3b9dac95a68c56e311b2113ac0ad590e1f4d25a8456f77c7edb0a32fc9e5f96

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=sha256:04ee985ebdb36cac81b9a348e61aa6a17a631589047e0c38d5d8fdb7d480c7e9

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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source=arxiv_source observed=2026-08-07T12:48:47.051024Z digest=sha256:59a701cea4c964086b0fcfba69cd5f01fd4d0d5cc4335b863358abdcbf3c7d11

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=sha256:49b8ad21c97ff41195cb5791dff3a45b6e961572867928220fc9b70f84753501

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=sha256:802319d373493cb66676fa8c7398d0ba180202bff06b4183d3c4c18e113d5ff3

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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source=arxiv_source observed=2026-08-07T10:44:59.314638Z digest=sha256:30e8a3cf84df924caec3eaf3ed867f3d92ddfe278eaf3183494e7da95721be34

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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source=pdf_text observed=2026-08-07T05:00:32.194052Z digest=sha256:83d1fbfa3e03d849ea162b8e99a73c2564c287e64972325709e9607c4a6a35c9

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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source=pdf_text observed=2026-08-07T05:01:08.038342Z digest=sha256:888c88da37d7aa28d9ae172acca7417beaa3b091ed480ce6ea029721ebf7c77c

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:d9c716f64db3c5bc8db1bba0acd42c68be6bcbedf47b975fabf973d3df1f175e

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:c75c2abd407e24c3983991f6b6d7cb9c97f8fea529326949924137bad7dab254

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=sha256:15acb831085583a6e9a9c710949b718d2accacf6948e9608798d5e259730dc15

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-21T23:36:12.949230Z digest=sha256:f998980bba88994094f2f8febb703636ffd8ffa0967c14009494bc092f00e0be

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:d24b027868b4e51a88314e5701a9eae3f224c07b3dc17d2d9907612de6ee4983

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=sha256:38b48bbe6486cef6b21aee552c3e31105adcff2d0d3a53894383d4ba3c20d57d

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:d05eda6b76aceaa572e6c4d778db76c45fa64be7775d9f7716e4300ad53f7734

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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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T06:39:42.391102Z digest=sha256:19ae60d4ce9df6f8d4246f62e9bd3f61b193b522058b32cda703b33de889d03f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T06:19:44.360734Z digest=sha256:6ae3bd08ed98932b153e129955919cd5ee8bab59010cbf19a7f2b6bff47c1a27

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T20:50:06.642976Z digest=sha256:77d48d8aef40b3001f53bc1a0134c3656d032e9d6df0e1e6f246e7f9947c1690

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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no resolver link, observed 2026-08-03T17:53:53.227185Z

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source=pdf_text observed=2026-08-03T17:53:53.227185Z digest=sha256:247810510afe85405b92b973d832ca8e85e98be38eb7a048a98276fa0478ddbb

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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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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T06:52:52.486546Z digest=sha256:be8a404d9561dfac67580d910ba2c99ffea66783235408c6bd8eca803cbf28bf

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

Source-reported events for the cited work

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T08:12:55.296932Z digest=sha256:ea24bacfffd94c3ea595c3473b2418a8fbdb025c77d7a5f9463d7c66785a1105

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

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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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T06:33:29.860024Z digest=sha256:11fcb60306a6ccd8b35985e5c01ac0a1cc5e3977925a1ff90de2e608e69dfd18

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T17:18:17.846140Z digest=sha256:c91a23af3e923f735402e321ea8a1d0590b05988e474c03cbd24520c22cbf929

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T03:45:06.199636Z digest=sha256:c91f693b7c7aa7beff386017bf9a4a154740c24cc626bb1eb1dfaffae80ae023

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

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T22:19:49.016156Z digest=sha256:3314e16db24ab4c416052b980a3d4b7003f66be201df41aafce95cf5159a2246

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

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T05:50:23.111591Z digest=sha256:7121f09ba319eba60738420866b80486f054efce7244684e5cc703115b3e547d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T06:33:36.835860Z digest=sha256:ad0f05eda1dce32051c98c6e7eaf7f41b5cf79b9e6991e211ba4d7a44c2f22c8

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T00:30:30.315423Z digest=sha256:239c18fcf5af3c09b498a45c13f3e6f0375602f59b851a48c30d3e0eafb2f11a

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-26T07:53:57.250401Z digest=sha256:6645da52ff9f506d7cc172edd43e593d0c3993b2be64b6e8b9446000a831e1b2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-30T10:13:09.503522Z digest=sha256:6c58601827df6438828a8fa99a04521cf509689df50057fa7ef2bf86b59289fc

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

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-02T19:21:44.653877Z digest=sha256:c6892acf04e5d1871ca03dedd8f4072abce595c6e0af26eee70d2c5de5ca48af

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-03T17:56:52.510949Z digest=sha256:ef1c93a5e329fa1f26f2da66216f5e076cf3b339d27863c8a3c1d9404b299e51

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:f54fec83c9e734197f7efac700b5a748a16fbc3f2c94557cf33f76b114a3d8ca

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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