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Paper Citation Record · LEDGER

MathPrompter: Mathematical Reasoning using Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 36 inbound Pith citation observations for arXiv:2303.05398.

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

pith.paper-citation-record.v1
2303.05398 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 36 of 36 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T23:21:56.461677Z

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

16
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 d4e8f48a-569d-49ad-ad50-9ae9b60f9a9d · inbound

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society cites this paper.

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society MathPrompter: Mathematical Reasoning using Large Language Models

Reference 52

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arxiv_id, observed 2026-05-14T01:40:53.878517Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T01:40:53.351795Z digest=sha256:48e65ceb79378c08aa201b55c10eab966d989f6d73768f2b526d8c5849e1fe0e

Observation bfca81c2-4609-4294-a141-0aedf0e43ccb · inbound

Agent AI: Surveying the Horizons of Multimodal Interaction cites this paper.

Agent AI: Surveying the Horizons of Multimodal Interaction MathPrompter: Mathematical Reasoning using Large Language Models

Reference 228

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arxiv_id, observed 2026-05-18T14:25:59.708896Z

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source=arxiv_source observed=2026-05-18T14:25:58.876978Z digest=sha256:88a6803b2a67c754d03dfe9d8e4306b8385fb7600b62db08397aa548763d5d73

Observation 9e199677-1e39-4492-b84e-84962e13fbaf · inbound

Efficient Causal Graph Discovery Using Large Language Models cites this paper.

Efficient Causal Graph Discovery Using Large Language Models MathPrompter: Mathematical Reasoning using Large Language Models

Reference 3

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arxiv_id, observed 2026-05-09T04:25:28.576059Z

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source=pdf_text observed=2026-05-24T04:10:17.251713Z digest=sha256:6e5f86d51ca7f64fc35f78e3a4cba369e00e2011b5bcc485a45b5f3ccd93fc5f

Observation dbb7d55e-dfbd-489d-8d1d-135f56d5402a · inbound

CodeMind: Evaluating Large Language Models for Code Reasoning cites this paper.

CodeMind: Evaluating Large Language Models for Code Reasoning MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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arxiv_id, observed 2026-05-24T03:55:59.730684Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T03:53:55.964755Z digest=sha256:53c036121917448e20a4baa2f63d4bb6e33f0a6c3eee1dd383579657c944ca10

Observation 25775b9d-291a-4cc8-a2c4-57b0c2623bf3 · inbound

A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models cites this paper.

A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models MathPrompter: Mathematical Reasoning using Large Language Models

Reference 16

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source=pdf_text observed=2026-08-09T23:21:56.461677Z digest=sha256:5ae0501d20d82618014f71b1de6ba8716c6f39f611078228838c2ceab55ed18c

Observation 96ef60d7-23ab-4c5a-bc0c-e3d7471451ca · inbound

LLMs can be easily Confused by Instructional Distractions cites this paper.

LLMs can be easily Confused by Instructional Distractions MathPrompter: Mathematical Reasoning using Large Language Models

Reference 14

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source=arxiv_source observed=2026-08-09T10:50:12.324974Z digest=sha256:f12405c756fe152dbeb97b203dc2baa24acfda7339281f99e1ee242e280cd1fc

Observation 0068c0bf-0aa0-4ea4-b5dd-c173fbdb980a · inbound

Active Task Disambiguation with LLMs cites this paper.

Active Task Disambiguation with LLMs MathPrompter: Mathematical Reasoning using Large Language Models

Reference 24

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source=arxiv_source observed=2026-08-08T22:38:19.894518Z digest=sha256:dbffbd34d271753e38e48a0a2e43b8612b8ccd5d514d6d56426fe62cdfc2d4b3

Observation 92f60199-3cc9-4cba-bd6d-e95807f96e7d · inbound

ZeroSearch: Incentivize the Search Capability of LLMs without Searching cites this paper.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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arxiv_id, observed 2026-05-17T17:44:13.457288Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T17:44:13.310155Z digest=sha256:f5cfea34885c1f84fd0cc021b680e895e17a37bcfe248a0605ec1db012c04e49

Observation ecbde63c-b3e4-46bb-87ea-b473e8a1299c · inbound

ZeroSearch: Incentivize the Search Capability of LLMs without Searching cites this paper.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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arxiv_id, observed 2026-05-22T16:06:45.894985Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T16:05:04.715678Z digest=sha256:13c36efa2e670ac8f4a6e492dd47fc2e82ff215a43338230cf7dbc847ae34eba

Observation 4a111b37-51f5-41c5-8693-1d7eec2198d8 · inbound

VLM-R$^3$: Region Recognition, Reasoning, and Refinement for Enhanced Multimodal Chain-of-Thought cites this paper.

VLM-R$^3$: Region Recognition, Reasoning, and Refinement for Enhanced Multimodal Chain-of-Thought MathPrompter: Mathematical Reasoning using Large Language Models

Reference 18

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source=pdf_text observed=2026-08-07T15:10:08.588351Z digest=sha256:cc69312316b225312ec43860bd8e7d66dbb9f9d58f66deb67d3f57086e8f275b

Observation c0bfeeb7-bbd4-4a89-a6c5-28b949708792 · inbound

Towards Objective Fine-tuning: How LLMs' Prior Knowledge Causes Potential Poor Calibration? cites this paper.

Towards Objective Fine-tuning: How LLMs' Prior Knowledge Causes Potential Poor Calibration? MathPrompter: Mathematical Reasoning using Large Language Models

Reference 18

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source=arxiv_source observed=2026-08-07T13:51:11.303922Z digest=sha256:b1b12eedf2f4f0a0d393a750eec4357df4656e47df4e7ff1b76300083827fac4

Observation d9da6d6b-e5f2-493f-abff-f5ae34c2f87d · inbound

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

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction MathPrompter: Mathematical Reasoning using Large Language Models

Reference 3

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arxiv_id, observed 2026-05-19T11:37:16.017673Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T11:34:09.428653Z digest=sha256:d8708ca867ec8b025e07be7a89095ec47f46effebd104c610dc51f9c9dec67ff

Observation 9ec5b8ff-bdb8-4a23-b3fe-d7cc9259516f · 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 MathPrompter: Mathematical Reasoning using Large Language Models

Reference 11

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source=arxiv_source observed=2026-08-07T10:59:04.705154Z digest=sha256:3fb42a20788c628c42048a39e5592a8f77a8c604b8cdc636b6f6f33391c90c6e

Observation aae6248f-6c2e-4532-87d2-64b77b41c189 · inbound

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

Structured Pruning for Diverse Best-of-N Reasoning Optimization MathPrompter: Mathematical Reasoning using Large Language Models

Reference 19

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source=arxiv_source observed=2026-08-07T10:56:23.586385Z digest=sha256:4d90de16fcf71a9afc2f93e7f30fbbf9bf19b1bc6313425ca2a82575ae900862

Observation ea991fb9-6da8-45a8-9831-72fc6250e744 · inbound

Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs cites this paper.

Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs MathPrompter: Mathematical Reasoning using Large Language Models

Reference 2023

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no resolver link, observed 2026-08-07T10:19:33.505707Z

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source=pdf_text observed=2026-08-07T10:19:33.505707Z digest=sha256:c81199fd0c35dbf3072b5b77aab1a74869863c738d45f465cdd18eec3d8c7c50

Observation 37a47894-4970-4e0a-8b98-74c3d3ee2f54 · inbound

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions cites this paper.

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions MathPrompter: Mathematical Reasoning using Large Language Models

Reference 62

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source=pdf_text observed=2026-08-07T05:42:30.983527Z digest=sha256:041171b75969646712780ae44120966d37eea841401cd54e86cd91e2ee152de6

Observation e363b9a7-d056-4a05-b06d-1aed85135f76 · 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 MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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source=arxiv_source observed=2026-08-06T22:21:10.269483Z digest=sha256:932bb97c6343364b240baca932a18115a19db9fcd07f668648bee51932339a90

Observation c7391140-c5ec-4f8f-88a8-320cd6003d9b · inbound

We Need Knowledge Distillation for Solving Math Word Problems cites this paper.

We Need Knowledge Distillation for Solving Math Word Problems MathPrompter: Mathematical Reasoning using Large Language Models

Reference 5

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source=pdf_text observed=2026-08-06T21:20:48.863797Z digest=sha256:80972af56ff6bb4b31256702534f0733e2a01e891762cd3f3f080a8d3234acd3

Observation ea2760e7-03f4-4799-ad2a-1a615e588236 · inbound

A Technical Survey of Reinforcement Learning Techniques for Large Language Models cites this paper.

A Technical Survey of Reinforcement Learning Techniques for Large Language Models MathPrompter: Mathematical Reasoning using Large Language Models

Reference 26

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source=pdf_text observed=2026-08-06T19:59:29.011036Z digest=sha256:95f8753a9ee81f9154ef77677eb5bb1f5c088a6ed40bcf7ed0ca0075574d4f68

Observation a812aa39-4782-4f0d-b5cf-a7fbfdec4854 · inbound

Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning cites this paper.

Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning MathPrompter: Mathematical Reasoning using Large Language Models

Reference 13

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source=arxiv_source observed=2026-08-06T17:52:36.093671Z digest=sha256:fd34fb572ad982c2f532d52ad6dde1c806822071abc77d1409e79d5b0324f53f

Observation 84645ec0-5c6d-40cd-9016-abb40f328580 · inbound

SVAgent: AI Agent for Hardware Security Verification Assertion cites this paper.

SVAgent: AI Agent for Hardware Security Verification Assertion MathPrompter: Mathematical Reasoning using Large Language Models

Reference 6

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no resolver link, observed 2026-08-06T15:22:32.883522Z

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source=pdf_text observed=2026-08-06T15:22:32.883522Z digest=sha256:621d9ba3975ea0bb30abd0183db783cd5f3c34968f4193bb0a3ab4448105b37d

Observation ee0752bb-ed3a-4021-a6b2-e540ccc3acbf · inbound

Can Structured Templates Facilitate LLMs in Tackling Harder Tasks? : An Exploration of Scaling Laws by Difficulty cites this paper.

Can Structured Templates Facilitate LLMs in Tackling Harder Tasks? : An Exploration of Scaling Laws by Difficulty MathPrompter: Mathematical Reasoning using Large Language Models

Reference 11

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no resolver link, observed 2026-08-05T16:02:03.315402Z

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source=pdf_text observed=2026-08-05T16:02:03.315402Z digest=sha256:b9b39c53e46dd2b135059b876ce15bdec4ab9e9210f1e07688d012c9ac2bf595

Observation 30564805-3eb1-4c07-9a99-5995ef44e848 · inbound

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs cites this paper.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs MathPrompter: Mathematical Reasoning using Large Language Models

Reference 8

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source=pdf_text observed=2026-08-04T23:56:34.886866Z digest=sha256:a7ad71a5d87ed5b1218462af02a004a7b2c24e865bcdee7970aad914a369b7d6

Observation 9f5d7f6f-e3a8-4454-a67d-a12e4f75834b · inbound

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences cites this paper.

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences MathPrompter: Mathematical Reasoning using Large Language Models

Reference 64

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arxiv_id, observed 2026-05-18T16:41:38.000449Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T16:39:03.794436Z digest=sha256:a61d26945e1b8286df4aa71759236baba76dcbec39456a02762d91a869a0d8b2

Observation 27aae890-d0eb-48a8-8555-c769c0ce2074 · inbound

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences cites this paper.

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences MathPrompter: Mathematical Reasoning using Large Language Models

Reference 65

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arxiv_id, observed 2026-05-18T16:41:37.666821Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T16:39:03.794436Z digest=sha256:670bca0392ae2b332a64c1ced9364f17b0cabbe4d11a68eb4acc041a2853e50a

Observation 99eff83d-25d0-4ec0-8426-5c114f2e8f28 · inbound

Learning How to Use Tools, Not Just When: Pattern-Aware Tool-Integrated Reasoning cites this paper.

Learning How to Use Tools, Not Just When: Pattern-Aware Tool-Integrated Reasoning MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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source=pdf_text observed=2026-08-04T14:49:51.572073Z digest=sha256:61b5b70b216cc8ef37ad1263e0840316df8935ec6aec6ec84357b6a463a57b7f

Observation eaa3ed97-99ee-416e-9116-57ac0385d855 · inbound

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models cites this paper.

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models MathPrompter: Mathematical Reasoning using Large Language Models

Reference 26

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arxiv_id, observed 2026-05-18T06:00:57.292158Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T05:59:00.400429Z digest=sha256:734e18d5f17ad3a58a8dffac96b1ca7bdabfb40289082bbbe7c7d549b3ef4888

Observation 23ec18a5-b313-4e6f-8ad4-5148f7ca3553 · inbound

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

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing MathPrompter: Mathematical Reasoning using Large Language Models

Reference 24

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arxiv_id, observed 2026-05-16T08:17:36.615429Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T08:12:55.296932Z digest=sha256:a04573c465093bd43594ae989f71145681299cc5f6c247fb8b719833ddc11c80

Observation e6c23e24-4aae-46b7-adc5-256afc7e1e13 · inbound

Context Learning for Multi-Agent Discussion cites this paper.

Context Learning for Multi-Agent Discussion MathPrompter: Mathematical Reasoning using Large Language Models

Reference 8

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arxiv_id, observed 2026-05-16T08:10:45.497307Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T08:08:39.182921Z digest=sha256:c245590e2d28ff568c82efc0fb0b04a8a48ac4372ebd445ba09d7bc82e167c6f

Observation be9d72b0-5d09-4624-a639-712d70c7d671 · inbound

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs cites this paper.

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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no resolver link, observed 2026-08-02T21:32:45.586588Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:32:45.586588Z digest=sha256:fb1cab2a7efcbc47dbb2510601d31adcb9a8045d85a5d61e404e18310fe22dcd

Observation 58bc0365-aa49-494a-a7c3-ff5f440dc0cd · inbound

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

Improving Medical VQA through Trajectory-Aware Process Supervision MathPrompter: Mathematical Reasoning using Large Language Models

Reference 9

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arxiv_id, observed 2026-05-11T07:06:06.713071Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:18:17.846140Z digest=sha256:f69b6a2836cdc415ac1cd752a358eb73aea01b8b90c783985c60aad29f49449c

Observation c09bb2e8-52d6-4df5-af70-9606b37cabd1 · inbound

Agentic Retrieval-Augmented Generation for Financial Document Question Answering cites this paper.

Agentic Retrieval-Augmented Generation for Financial Document Question Answering MathPrompter: Mathematical Reasoning using Large Language Models

Reference 14

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arxiv_id, observed 2026-05-11T17:51:08.321564Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T17:03:09.496490Z digest=sha256:89146b3dcbce9ee721ccffa29f3e2f9748dceb7b1eb98839b6e499f2c7f1893c

Observation 53a1eed5-dda2-4945-aee3-4ba683be272f · inbound

SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model cites this paper.

SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

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arxiv_id, observed 2026-05-11T04:30:55.975142Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T01:19:42.892343Z digest=sha256:ef601075e903b8df3b98107ec2597069f0ab19a491ab7a4501d4cb369d141a7d

Observation 593919cb-2f22-4a20-87e6-1cf1d017f71c · inbound

Adaptive Order Policies for Masked Diffusion cites this paper.

Adaptive Order Policies for Masked Diffusion MathPrompter: Mathematical Reasoning using Large Language Models

Reference 90

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arxiv_id, observed 2026-06-28T23:42:49.871113Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T23:33:40.937370Z digest=sha256:d0b91376ed49b6eb37bf5e6fbfe1c39aa7d4b38056bc187b096c95474501cd1a

Observation 9a0da260-5d7c-42e6-80ad-974eadc0fe48 · inbound

GSM-Plus-BN: A Perturbation-Based Benchmark for Bangla Mathematical Reasoning in Large Language Models cites this paper.

GSM-Plus-BN: A Perturbation-Based Benchmark for Bangla Mathematical Reasoning in Large Language Models MathPrompter: Mathematical Reasoning using Large Language Models

Reference 55

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Explaining and Tuning Transformer-based LLMs in Arithmetic Tasks with Human Strategies cites this paper.

Explaining and Tuning Transformer-based LLMs in Arithmetic Tasks with Human Strategies MathPrompter: Mathematical Reasoning using Large Language Models

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