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Paper Citation Record · LEDGER

Solving Quantitative Reasoning Problems with Language Models

As of 16 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 100 inbound Pith citation observations for arXiv:2206.14858.

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

pith.paper-citation-record.v1
2206.14858 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T22:43:59.365155Z

measured 113 of 113 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 100 of 101 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:00:20.438677Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

281
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 928ddd2b-7c2b-461a-8353-f758c09d37e5 · outbound

This paper cites math/latex.

Solving Quantitative Reasoning Problems with Language Models math/latex

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:d122c1338c4f5deac6d6d13d6393a2c8f600acca5cd313de7e337de1aefbb232

Observation fad014b5-e848-4682-815e-2e64f0e3bea7 · outbound

This paper cites application/x-tex.

Solving Quantitative Reasoning Problems with Language Models application/x-tex

Reference 2

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raw_fallback, observed 2026-05-12T22:43:59.397525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:1e0a6f7de34bc14882252e1e5f4855576654222105cc294cf2b098f969cfb6c7

Observation 6c20835f-4a4d-413e-98d1-b75d648de335 · outbound

This paper cites Model output (62B):The sum of the geometric series is 0.12 1−0.12 = 1/2 1−1/2 = 1/2 1/2 = 1.

Solving Quantitative Reasoning Problems with Language Models Model output (62B):The sum of the geometric series is 0.12 1−0.12 = 1/2 1−1/2 = 1/2 1/2 = 1

Reference 3

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:3f02f3efed174ef544e6dc4fb51f7212f76a4c72b617a235ecf0484bfc0ec60e

Observation a872de3a-8d44-446c-a252-b352d2486bf5 · outbound

This paper cites Misunderstanding of a problem statement.

Solving Quantitative Reasoning Problems with Language Models Misunderstanding of a problem statement

Reference 4

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raw_fallback, observed 2026-05-12T22:43:59.406879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:662a275cd0585277752fa9def915a3d8f5d7c9dd9363af965c863d540075f160

Observation ba2bc752-2d77-4d65-b185-3648f64c3acb · outbound

This paper cites Model output (8B):We have that the lines are parallel if their slopes are the same.

Solving Quantitative Reasoning Problems with Language Models Model output (8B):We have that the lines are parallel if their slopes are the same

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:24993d361f04d152d68591e604cb5aa5d8932fd0ab0e9b50a627e845f09b1b0d

Observation 2c83853d-dc2e-4bd1-ad9e-1179761cd730 · outbound

This paper cites an unresolved cited work.

Solving Quantitative Reasoning Problems with Language Models Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:fc2053943ee320062fa09c8046394a9269d0518bd6bf6bbda9c7c39810551362

Observation 8b1af424-066a-4310-827d-93684a056d6f · outbound

This paper cites Question: Find the product10· 4 3· 6 4· 8 5· 10 6 · 12 7 · 14 8 · 16 9 · 18 10.

Solving Quantitative Reasoning Problems with Language Models Question: Find the product10· 4 3· 6 4· 8 5· 10 6 · 12 7 · 14 8 · 16 9 · 18 10

Reference 7

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Observation 0da83e5d-0989-4cc0-9a30-3f90f0645f93 · outbound

This paper cites Model output: The first perfect cube in the list is253 = 15625.

Solving Quantitative Reasoning Problems with Language Models Model output: The first perfect cube in the list is253 = 15625

Reference 8

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T22:43:59.365155Z digest=sha256:7dd31a852363ca1005faef0985d1a506210c9096dd94878d9531fcb41bec1d18

Observation 4b9b0b1a-bfaa-47d5-a7d9-553a21637979 · outbound

This paper cites an unresolved cited work.

Solving Quantitative Reasoning Problems with Language Models Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0710a3e4-29d8-4d3d-b5f8-0ef94cbb2929 · outbound

This paper cites Final solution: The final answer is2 3.

Solving Quantitative Reasoning Problems with Language Models Final solution: The final answer is2 3

Reference 10

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 81b27b7e-377d-4a41-a8e3-a41785c11715 · outbound

This paper cites Final solution: The final answer is30 √ 3.

Solving Quantitative Reasoning Problems with Language Models Final solution: The final answer is30 √ 3

Reference 11

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raw_fallback, observed 2026-05-12T22:43:59.445662Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a57a4c8b-76c1-46c4-86f5-34d025ff4f4c · outbound

This paper cites Model output - 540B:We will haven×m = 24 if and only ifn = 3 and m = 8, or ifn = 4 and m = 6, or ifn = 6 and m = 4, or ifn = 8 and m = 3.

Solving Quantitative Reasoning Problems with Language Models Model output - 540B:We will haven×m = 24 if and only ifn = 3 and m = 8, or ifn = 4 and m = 6, or ifn = 6 and m = 4, or ifn = 8 and m = 3

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 6edbfe57-9c70-4a1a-b051-21e06adf8866 · outbound

This paper cites Large model [correct]:We will haven×m = 24 if and only ifn = 3 and m = 8, or ifn = 4 and m = 6, or ifn = 6 and m = 4, or ifn = 8 and m = 3.

Solving Quantitative Reasoning Problems with Language Models Large model [correct]:We will haven×m = 24 if and only ifn = 3 and m = 8, or ifn = 4 and m = 6, or ifn = 6 and m = 4, or ifn = 8 and m = 3

Reference 13

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raw_fallback, observed 2026-05-12T22:43:59.457462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

Observation 391f3aa2-a8aa-4d19-ab72-25179572295a · inbound

PaLM: Scaling Language Modeling with Pathways cites this paper.

PaLM: Scaling Language Modeling with Pathways Solving Quantitative Reasoning Problems with Language Models

Reference 86

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e02e2515-f470-4dd3-ad04-0c73156464ea · inbound

Code as Policies: Language Model Programs for Embodied Control cites this paper.

Code as Policies: Language Model Programs for Embodied Control Solving Quantitative Reasoning Problems with Language Models

Reference 44

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local_arxiv, observed 2026-05-15T00:38:02.847224Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c9d67503-cf1a-4df1-95c4-462192391825 · inbound

Galactica: A Large Language Model for Science cites this paper.

Galactica: A Large Language Model for Science Solving Quantitative Reasoning Problems with Language Models

Reference 43

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local_arxiv, observed 2026-05-13T05:53:21.992697Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation afe5d696-79ca-4ecb-928d-119ca421fe64 · inbound

Galactica: A Large Language Model for Science cites this paper.

Galactica: A Large Language Model for Science Solving Quantitative Reasoning Problems with Language Models

Reference 200

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5442122b-2a04-4182-bc58-bfb4b0f97498 · inbound

PAL: Program-aided Language Models cites this paper.

PAL: Program-aided Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 19

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a31305ee-9b1f-4320-8dd9-4ada845b17b6 · inbound

Solving math word problems with process- and outcome-based feedback cites this paper.

Solving math word problems with process- and outcome-based feedback Solving Quantitative Reasoning Problems with Language Models

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d2c7414a-13ce-438c-b0be-6a901b70ffa2 · inbound

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning cites this paper.

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning Solving Quantitative Reasoning Problems with Language Models

Reference 31

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local_arxiv, observed 2026-05-24T09:14:16.398437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 01278255-d868-4db2-b19b-803b333fe507 · inbound

PaLM-E: An Embodied Multimodal Language Model cites this paper.

PaLM-E: An Embodied Multimodal Language Model Solving Quantitative Reasoning Problems with Language Models

Reference 19

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 39cd907c-edf6-495c-beed-0265ba6a244c · inbound

BloombergGPT: A Large Language Model for Finance cites this paper.

BloombergGPT: A Large Language Model for Finance Solving Quantitative Reasoning Problems with Language Models

Reference 65

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local_arxiv, observed 2026-05-13T23:19:46.723111Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f53324cb-6e7e-4e70-bf53-0a778fab8b12 · inbound

A Survey of Large Language Models cites this paper.

A Survey of Large Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 222

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5112874c-21c1-4624-9757-31f1d33464bd · inbound

Towards Expert-Level Medical Question Answering with Large Language Models cites this paper.

Towards Expert-Level Medical Question Answering with Large Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 19

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local_arxiv, observed 2026-05-24T04:32:33.426530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-24T04:32:33.271634Z digest=sha256:1362c130174256383fe9c43f7a9a4f86bc8f7568b8513d9eb432e890ce8596a7

Observation 6e1b2c16-a90a-4dfc-b60c-e6b26514a52a · inbound

PaLM 2 Technical Report cites this paper.

PaLM 2 Technical Report Solving Quantitative Reasoning Problems with Language Models

Reference 245

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arxiv_id, observed 2026-05-12T22:43:59.458883Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0e60ad0f-9e08-45dc-aed1-35e2d1bd970b · inbound

Improving Factuality and Reasoning in Language Models through Multiagent Debate cites this paper.

Improving Factuality and Reasoning in Language Models through Multiagent Debate Solving Quantitative Reasoning Problems with Language Models

Reference 13

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arxiv_id, observed 2026-05-12T22:43:59.458883Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 71f3a511-f33c-4342-a78c-a041b17bdbb4 · inbound

Reasoning with Language Model is Planning with World Model cites this paper.

Reasoning with Language Model is Planning with World Model Solving Quantitative Reasoning Problems with Language Models

Reference 115

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local_arxiv, observed 2026-05-17T01:49:28.893305Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8896b255-4320-4996-ae80-ec58e387b531 · inbound

Let's Verify Step by Step cites this paper.

Let's Verify Step by Step Solving Quantitative Reasoning Problems with Language Models

Reference 9

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arxiv_id, observed 2026-05-12T22:43:59.458883Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation ccdffaa8-3556-44cd-b9c1-2fc90b6f605d · inbound

Simple synthetic data reduces sycophancy in large language models cites this paper.

Simple synthetic data reduces sycophancy in large language models Solving Quantitative Reasoning Problems with Language Models

Reference 18

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3ee246bc-cae0-441f-ae14-6643ce1e4bee · inbound

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling cites this paper.

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling Solving Quantitative Reasoning Problems with Language Models

Reference 43

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arxiv_id, observed 2026-05-12T22:43:59.458883Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b936ff09-3887-48b4-9ff5-c3e429fdd334 · inbound

Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models cites this paper.

Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 62

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local_arxiv, observed 2026-05-15T09:09:15.015382Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5108ad20-4c4f-445d-9c96-9be0e5fb50da · inbound

Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training cites this paper.

Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training Solving Quantitative Reasoning Problems with Language Models

Reference 21

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0cdd669-d539-4bf8-9289-cf64e56cf69d · inbound

Dynamic Skill Adaptation for Large Language Models cites this paper.

Dynamic Skill Adaptation for Large Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 78ede9c0-1df4-4652-973a-b0e38de329d3 · inbound

A Survey on Large Language Models with some Insights on their Capabilities and Limitations cites this paper.

A Survey on Large Language Models with some Insights on their Capabilities and Limitations Solving Quantitative Reasoning Problems with Language Models

Reference 187

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no resolver link, observed 2026-08-10T22:17:56.102902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 633e2d24-af07-442e-9683-0127106f4bc0 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 87

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local_arxiv, observed 2026-05-23T04:32:33.255944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:015397ce28ed18e0a1866857d69743f0c8afb8f6d39d5956420e37030990cf21

Observation 25f16854-530d-4160-9582-d0604e29c8f3 · inbound

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach cites this paper.

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach Solving Quantitative Reasoning Problems with Language Models

Reference 93

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arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-12T15:39:40.845703Z digest=sha256:d7be3b408f2bd7acc8799256a29271d8d73625ce2372c7a2d311fe01dc0e46d0

Observation 6ac1d63d-bc78-46a4-ada3-ec449e181772 · inbound

Fino1: On the Transferability of Reasoning-Enhanced LLMs and Reinforcement Learning to Finance cites this paper.

Fino1: On the Transferability of Reasoning-Enhanced LLMs and Reinforcement Learning to Finance Solving Quantitative Reasoning Problems with Language Models

Reference 16

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no resolver link, observed 2026-08-08T10:25:12.994154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:25:12.994154Z digest=sha256:c3b4d640fdff89ea17f1cdb1daf065ed1a0d2252b18930f26a6746b9d3c34980

Observation d8c04222-da3e-444d-b7b9-697610f088e4 · inbound

Learning to Reason at the Frontier of Learnability cites this paper.

Learning to Reason at the Frontier of Learnability Solving Quantitative Reasoning Problems with Language Models

Reference 25

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verified exact
local_arxiv, observed 2026-05-23T02:42:26.053039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-23T02:41:21.571824Z digest=sha256:c9cb4504e1b4230b983508134d9bfcf725602d31390960690f0c9517991b7dd4

Observation af5e6269-2f9d-42ae-a11e-dbd98f96949a · inbound

Towards an AI co-scientist cites this paper.

Towards an AI co-scientist Solving Quantitative Reasoning Problems with Language Models

Reference 102

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arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-11T13:02:43.571234Z digest=sha256:cccce4c4f8af1ac4c2a9372b8485c85903cb6e52e4715805acb11fd676ba9d49

Observation 128d52c0-5ac5-4988-a925-4f3ec5647cb1 · inbound

PRIMETIME : Limits of LLMs in Temporal Primitives cites this paper.

PRIMETIME : Limits of LLMs in Temporal Primitives Solving Quantitative Reasoning Problems with Language Models

Reference 107

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local_arxiv, observed 2026-05-22T18:36:58.923453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-22T18:36:48.376877Z digest=sha256:518b35951bb30c2cb0bd3807002483cb5b33ffe4594eee6a94f777342de5c0f9

Observation 5742344d-f9f6-4aff-a6c6-5f1ad4cf92ea · inbound

Lightweight Latent Verifiers for Efficient Meta-Generation Strategies cites this paper.

Lightweight Latent Verifiers for Efficient Meta-Generation Strategies Solving Quantitative Reasoning Problems with Language Models

Reference 30

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unresolved
no resolver link, observed 2026-08-16T11:00:20.438677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:00:20.438677Z digest=sha256:da0e416bb1d126e3c85c8bd71c31ea04f22b154e8e21e3aa74fab5366712718d

Observation a782e00d-e4d6-4a23-bb08-1c62c9eeeb19 · inbound

Think, Prune, Train, Improve: Scaling Reasoning without Scaling Models cites this paper.

Think, Prune, Train, Improve: Scaling Reasoning without Scaling Models Solving Quantitative Reasoning Problems with Language Models

Reference 12

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unresolved
no resolver link, observed 2026-08-16T10:29:18.710012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:29:18.710012Z digest=sha256:b06dfbfe60ccce6c99cc8888edde4bfba114c44b279843383650bddb9988159c

Observation bdc565e9-c62e-4427-a3a6-79759c729118 · inbound

Beyond Theorem Proving: Formulation, Framework and Benchmark for Formal Problem-Solving cites this paper.

Beyond Theorem Proving: Formulation, Framework and Benchmark for Formal Problem-Solving Solving Quantitative Reasoning Problems with Language Models

Reference 20

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no resolver link, observed 2026-08-15T23:31:49.328809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:31:49.328809Z digest=sha256:57020b41213b47e30c8b1d991b1ac59b7c47a7b93c8207f758ddf7d9f9d760ac

Observation 9a8e00ab-e919-4b77-8a3e-ac4f8a75fbdd · inbound

Scalable Chain of Thoughts via Elastic Reasoning cites this paper.

Scalable Chain of Thoughts via Elastic Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 15

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no resolver link, observed 2026-08-15T23:13:33.107297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:13:33.107297Z digest=sha256:19428f85b2cf8b2a5b2e308600144b266dac9e2db4e8eba7cb2de7e7f77eac6e

Observation 08b909eb-c446-4310-874f-c139ec93cb6b · inbound

Parallel Scaling Law for Language Models cites this paper.

Parallel Scaling Law for Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 46

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no resolver link, observed 2026-08-15T21:14:45.693699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:14:45.693699Z digest=sha256:037294960e86c6df69d1682958eb9bb598a1b1614966a75e07ffd65fd597288f

Observation 558a436b-7883-4f23-8d1c-99f72a9d1a48 · inbound

SCOPE: Compress Mathematical Reasoning Steps for Efficient Automated Process Annotation cites this paper.

SCOPE: Compress Mathematical Reasoning Steps for Efficient Automated Process Annotation Solving Quantitative Reasoning Problems with Language Models

Reference 11

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no resolver link, observed 2026-08-07T15:39:17.342085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:39:17.342085Z digest=sha256:9d4bc438caed3c3ffe0ab054cc79a96461c92f9360220af6f65e4a477ac1fc43

Observation ec49cccf-7992-40b4-a64d-5ecc9d347567 · inbound

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models cites this paper.

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 31

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no resolver link, observed 2026-08-07T14:46:16.437950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:16.437950Z digest=sha256:b46903f4322fd41ae8bcc39bec558ef5393d4942f1d894e7b76ca62f2ddeb79d

Observation 0abd8209-5321-49c0-9ed2-e728d7f31d22 · inbound

RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion cites this paper.

RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion Solving Quantitative Reasoning Problems with Language Models

Reference 12

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no resolver link, observed 2026-08-07T14:45:59.385710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:45:59.385710Z digest=sha256:7935c02867b35cb014f38df666e677165bcbfcc4f778500babfba490b3f29883

Observation 7ff258c3-e82b-42e2-a58b-d3e9d85fff9c · inbound

Breakpoint: Scalable evaluation of system-level reasoning in LLM code agents cites this paper.

Breakpoint: Scalable evaluation of system-level reasoning in LLM code agents Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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no resolver link, observed 2026-08-07T12:17:44.675554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:17:44.675554Z digest=sha256:a43fc960618df843c7025bae5fa27a53b9bdefd4159ff846eacdc7ee4cf6e528

Observation 84f36c0b-d4ae-4b19-831f-94efbc16a9f8 · inbound

RewardBench 2: Advancing Reward Model Evaluation cites this paper.

RewardBench 2: Advancing Reward Model Evaluation Solving Quantitative Reasoning Problems with Language Models

Reference 66

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verified exact
local_arxiv, observed 2026-05-19T11:22:16.703008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-19T11:18:03.965711Z digest=sha256:3cb699527a586dad97206372eea191f0a5e5f5a6af43797c4f5cc7f1293c45a3

Observation c3d58d4a-3f9b-41c4-94ad-867c9c85e6f1 · 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 Solving Quantitative Reasoning Problems with Language Models

Reference 22

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no resolver link, observed 2026-08-07T11:33:31.305077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:31.305077Z digest=sha256:80f4b716ad77cadc48ebf8db4d2886c873b8523cd1cea976efdadf8074edc204

Observation 6af3ac2c-237a-4e9b-b519-5de7d147b83d · inbound

Progressive Mastery: Customized Curriculum Learning with Guided Prompting for Mathematical Reasoning cites this paper.

Progressive Mastery: Customized Curriculum Learning with Guided Prompting for Mathematical Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 13

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no resolver link, observed 2026-08-07T10:54:07.774895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:54:07.774895Z digest=sha256:bfc2c98ede0df21490df09598c47f27730b1d0999327508220e3c78ee5917a91

Observation d09a825c-5489-4883-9108-1d19d919c400 · inbound

How Far Are We from Optimal Reasoning Efficiency? cites this paper.

How Far Are We from Optimal Reasoning Efficiency? Solving Quantitative Reasoning Problems with Language Models

Reference 17

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no resolver link, observed 2026-08-07T05:49:36.305178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:49:36.305178Z digest=sha256:7aadff39f4d825725c693373aceddb807881bc87c3bf429b4a64a9b8f352b063

Observation d380343b-e0fa-4e43-85c3-f8f5eb1ed691 · inbound

A Survey on Large Language Models for Mathematical Reasoning cites this paper.

A Survey on Large Language Models for Mathematical Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 51

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no resolver link, observed 2026-08-07T05:14:47.319519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:47.319519Z digest=sha256:8b19bb0e68f9fc9d80942d085b3f9394696f384f16f414b93e2f8c00c7769c2b

Observation 50b2e901-02a1-4f37-904a-fa46d9a881be · inbound

Can A Gamer Train A Mathematical Reasoning Model? cites this paper.

Can A Gamer Train A Mathematical Reasoning Model? Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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no resolver link, observed 2026-08-07T05:03:21.738356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:03:21.738356Z digest=sha256:1a73406d0e304ec6c1b73378931e9681b1d05cb205299f26b82d51c8c6549401

Observation ff3f062b-a510-4fb4-a47e-b4f2e32cd0a3 · inbound

RLPR: Extrapolating RLVR to General Domains without Verifiers cites this paper.

RLPR: Extrapolating RLVR to General Domains without Verifiers Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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no resolver link, observed 2026-08-15T19:01:06.292222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:01:06.292222Z digest=sha256:7d27a5c67bafd6544b57a42d2827ef5d06dfd6f6736fb29d7e483d28ced49174

Observation accf01ce-e8e2-4f4e-9c75-2fc42dac7d20 · inbound

Do Thinking Tokens Help or Trap? Towards More Efficient Large Reasoning Model cites this paper.

Do Thinking Tokens Help or Trap? Towards More Efficient Large Reasoning Model Solving Quantitative Reasoning Problems with Language Models

Reference 15

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no resolver link, observed 2026-08-06T21:45:08.187391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:45:08.187391Z digest=sha256:d2eac973b1b101978dc9c4737d03a6c20ed680dc3933f00d9d321d7cc702ba0a

Observation 4a12c555-c014-4f5d-882d-07a006bbcb36 · inbound

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization cites this paper.

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization Solving Quantitative Reasoning Problems with Language Models

Reference 23

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no resolver link, observed 2026-08-06T19:14:16.385011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:14:16.385011Z digest=sha256:d427c87e871fb29ff9561e0fdb984448682d12f54a3ac4a699b8f25de553225a

Observation 5e71face-cb27-4ca1-baa1-71adfac923c3 · inbound

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey cites this paper.

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey Solving Quantitative Reasoning Problems with Language Models

Reference 93

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no resolver link, observed 2026-08-06T17:54:16.964248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:54:16.964248Z digest=sha256:63a0a4b28f63773a28a4badb49c55eb2aeef95e83ae84663cacf47d712358cad

Observation 5a21e266-f982-45af-b54a-c35634c4fe36 · inbound

Which LLMs Get the Joke? Probing Non-STEM Reasoning Abilities with HumorBench cites this paper.

Which LLMs Get the Joke? Probing Non-STEM Reasoning Abilities with HumorBench Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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unresolved
no resolver link, observed 2026-08-06T12:48:08.040390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:48:08.040390Z digest=sha256:c06a6bedeee759148b96c7205631e82b5d8a780e8a6c1cea53ce241029e42727

Observation 83f14dab-ca0d-4b49-8f7d-1a69efff6c58 · inbound

EDGE-GRPO: Entropy-Driven GRPO with Guided Error Correction for Advantage Diversity cites this paper.

EDGE-GRPO: Entropy-Driven GRPO with Guided Error Correction for Advantage Diversity Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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no resolver link, observed 2026-08-06T12:26:11.155945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:26:11.155945Z digest=sha256:d18be33dfdd5e62ef04aa5d4842ae7819fe25da352ad864cdb140b0b65f09818

Observation 65d90a86-b989-419c-92b8-db89f68b9bff · inbound

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation cites this paper.

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation Solving Quantitative Reasoning Problems with Language Models

Reference 30

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unresolved
no resolver link, observed 2026-08-15T17:21:06.713094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:21:06.713094Z digest=sha256:9ccd7f48e323c3ded3cc0c4bf9b869449b0471bdc550f3941d5351bddae0c689

Observation 07a747b6-ef1f-47df-954c-57f9e7ea8c02 · inbound

Language Models Coupled with Metacognition Can Outperform Reasoning Models cites this paper.

Language Models Coupled with Metacognition Can Outperform Reasoning Models Solving Quantitative Reasoning Problems with Language Models

Reference 28

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no resolver link, observed 2026-08-15T17:03:44.040662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:03:44.040662Z digest=sha256:30705d6656a041a307ed547d4718b95119b02dd3386bcdc9d4852fc5c47bf369

Observation cc3b578e-4cf2-4520-aef8-505414412de6 · inbound

RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning cites this paper.

RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 10

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no resolver link, observed 2026-08-04T21:54:48.197117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T21:54:48.197117Z digest=sha256:53899fb49aefb3ecd7f3b264c20b26d06579cd080f079eaebcde8f8c4a3e456c

Observation be266653-374b-4415-9b15-43a892a8c35e · inbound

SoM-1K: A Thousand-Problem Benchmark Dataset for Strength of Materials cites this paper.

SoM-1K: A Thousand-Problem Benchmark Dataset for Strength of Materials Solving Quantitative Reasoning Problems with Language Models

Reference 21

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no resolver link, observed 2026-08-15T15:49:57.000317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T15:49:57.000317Z digest=sha256:437c1eb7218ddfb6f29f6f70e09e56444a2914cab089cb86d5465eb1f14e7b98

Observation a6fa7254-93ae-453e-b732-8cbf73c1e452 · inbound

Rethinking RL Evaluation: Can Benchmarks Truly Reveal Failures of RL Methods? cites this paper.

Rethinking RL Evaluation: Can Benchmarks Truly Reveal Failures of RL Methods? Solving Quantitative Reasoning Problems with Language Models

Reference 5

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unresolved
no resolver link, observed 2026-08-04T10:20:18.458587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:20:18.458587Z digest=sha256:ba81499a83c8b8b792b7c7011bddb2895258d77286e254b333be221760f26925

Observation 35273487-6d54-4493-aa0e-a10989e94339 · inbound

MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation cites this paper.

MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation Solving Quantitative Reasoning Problems with Language Models

Reference 27

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unresolved
no resolver link, observed 2026-08-04T08:55:58.655096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:55:58.655096Z digest=sha256:7858ddaf5b3901843054aa2e5a67b80a67c3d92806e31d2baa12266d02c2cfe4

Observation 30ed0407-feea-4758-b574-f82ca49c3b9a · inbound

GraphMind: Theorem Selection and Conclusion Generation Framework with Dynamic GNN for LLM Reasoning cites this paper.

GraphMind: Theorem Selection and Conclusion Generation Framework with Dynamic GNN for LLM Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 17

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metadata mismatch
local_arxiv, observed 2026-05-21T18:34:17.971557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T18:31:46.510611Z digest=sha256:4e8a7ea9e31b606188cd0af499c520324d7d652b90b8581c06700334f7dfd9e9

Observation f7005529-7fb1-4a36-b662-b98b6f419f79 · inbound

DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training cites this paper.

DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training Solving Quantitative Reasoning Problems with Language Models

Reference 14

Resolution
metadata mismatch
local_arxiv, observed 2026-05-17T01:48:51.106437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-17T01:46:21.744857Z digest=sha256:fc77d0c41c2b89cbeea91d236b26d5be18f65ad1d26b2414e8ba14ae2e3293d8

Observation 97bd76e7-e889-42b1-b1f3-f9da977d1afa · inbound

Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning cites this paper.

Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 20

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verified exact
local_arxiv, observed 2026-05-16T22:43:37.841057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-16T22:43:01.937642Z digest=sha256:4988ed3b7b3a70dacb7a6dca9cb5ec0c1557b0f45f19ee12c14613541ea994ad

Observation 6c5b8c08-1601-4292-88d2-341ce52d9524 · inbound

Coupled Variational Reinforcement Learning for Language Model General Reasoning cites this paper.

Coupled Variational Reinforcement Learning for Language Model General Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 10

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no resolver link, observed 2026-08-03T16:43:55.364185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:43:55.364185Z digest=sha256:d44b85f6b7dae8af9fe897b60b0cd49c0061cf9b367a59f6caac2aaa38bb26dc

Observation f51cda2a-2faa-405b-9701-30a67dc53431 · inbound

CORE: Concept-Oriented Reinforcement for Bridging the Definition-Application Gap in Mathematical Reasoning cites this paper.

CORE: Concept-Oriented Reinforcement for Bridging the Definition-Application Gap in Mathematical Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-05-16T20:28:24.126245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-16T20:25:35.573805Z digest=sha256:bdd2490ceffb6d7eb3b6125d4d2d5abb52e0e93c32e9178a0a6a3fc3192fb424

Observation 4a88acd3-be15-493f-a424-bfa82670cc09 · inbound

Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMs cites this paper.

Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMs Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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no resolver link, observed 2026-08-03T10:13:14.751527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:13:14.751527Z digest=sha256:ae561eadac80723af9f3f5d0bdc22438fe4ec767339ecf6fb22bb61fec2a478e

Observation c7a19091-6e30-466f-9050-cb40ebc128d1 · inbound

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning cites this paper.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Solving Quantitative Reasoning Problems with Language Models

Reference 21

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unresolved
no resolver link, observed 2026-08-03T05:14:19.142903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T05:14:19.142903Z digest=sha256:bb83628b3ed3a05798f3390e04b4b0e84e4bb41e1337bb60560e6e9c62097d7b

Observation 4d6598c9-fd54-434a-a830-8d18c221cd80 · inbound

When LLMs get significantly worse: A statistical approach to detect model degradations cites this paper.

When LLMs get significantly worse: A statistical approach to detect model degradations Solving Quantitative Reasoning Problems with Language Models

Reference 6

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verified exact
local_arxiv, observed 2026-05-16T06:07:25.809903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-16T06:03:37.788377Z digest=sha256:961a204f34bf400e1130254bdb65cd803b2b792bfabac53547ce252f077298e6

Observation 525c5edd-54fd-4ea3-8071-1cf2c1945008 · inbound

When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation cites this paper.

When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation Solving Quantitative Reasoning Problems with Language Models

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-02T22:31:49.798678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:31:49.798678Z digest=sha256:68e7b2fb5e3502d2b1123e81402d40585ba3315520e3fbb173c5d38f449c8374

Observation 976d3e42-df8e-4b85-ae02-a6940dc370c6 · inbound

Boosting MLLM Spatial Reasoning with Geometrically Referenced 3D Scene Representations cites this paper.

Boosting MLLM Spatial Reasoning with Geometrically Referenced 3D Scene Representations Solving Quantitative Reasoning Problems with Language Models

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-05-15T14:35:56.065052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-15T14:31:03.909336Z digest=sha256:3d52e942debadbecabd610388acc4c4314817c755be8534cfba2689f75b55b13

Observation a7b4be31-3d19-483a-8913-66bb55cd7d0e · inbound

Attention Residuals cites this paper.

Attention Residuals Solving Quantitative Reasoning Problems with Language Models

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-05-21T06:39:04.500945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T06:39:04.312270Z digest=sha256:6a55c68629cbe78077cba38194ea135e1f65ff1752704c6ff63e3091e621f0ba

Observation c75d1cd3-2d6c-4431-97fb-f713846ce7e7 · inbound

Assessing Large Language Models for Stabilizing Numerical Expressions in Scientific Software cites this paper.

Assessing Large Language Models for Stabilizing Numerical Expressions in Scientific Software Solving Quantitative Reasoning Problems with Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T19:18:06.308941Z digest=sha256:921d343b56e4037aa6d1983925fb9add7c2f569de7424fdcaadb628277f6d3c8

Observation dda7c15a-ae62-4d17-87f1-672a2e1d1707 · inbound

The Master Key Hypothesis: Unlocking Cross-Model Capability Transfer via Linear Subspace Alignment cites this paper.

The Master Key Hypothesis: Unlocking Cross-Model Capability Transfer via Linear Subspace Alignment Solving Quantitative Reasoning Problems with Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T18:36:44.401045Z digest=sha256:de1400fe7004c9dcf888e8bf5d54a62035185e126a5fcd18c276ccfabc3281d5

Observation bbabaafc-dd92-409f-a2b1-a55162726dc8 · inbound

From Perception to Autonomous Computational Modeling: A Multi-Agent Approach cites this paper.

From Perception to Autonomous Computational Modeling: A Multi-Agent Approach Solving Quantitative Reasoning Problems with Language Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T17:54:40.177049Z digest=sha256:e3e0ca2f465822d79727859a97db29065147c111b97e8fc617f2180636744b29

Observation 8bd07ec3-655d-4c5e-84b1-1a69196829ea · inbound

When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning cites this paper.

When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T18:40:04.944348Z digest=sha256:af7d533cd1aea0345d98b17a1adeba0cb36474b7e134b4255f4c9b6327753c61

Observation 8181b803-58df-495b-bc2e-104fe803fa31 · inbound

Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models cites this paper.

Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T17:27:37.161657Z digest=sha256:f1c35047aff13a73ec6539399509fbb0bd0910c171b73a30f54c139e5e1c4def

Observation 160dda99-d944-4d04-ae55-3a6a34ae75ca · inbound

Measuring Representation Robustness in Large Language Models for Geometry cites this paper.

Measuring Representation Robustness in Large Language Models for Geometry Solving Quantitative Reasoning Problems with Language Models

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-13T19:38:10.475735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-13T19:35:32.531660Z digest=sha256:80c91192c4b865bc0cc43d9eeecf8038c5d60d48f71b87fa7a5ea8cf1c5eb0b1

Observation f2dce326-f17c-4651-8365-86f0e9ced5b2 · inbound

Multiplication in Multimodal LLMs: Computation with Text, Image, and Audio Inputs cites this paper.

Multiplication in Multimodal LLMs: Computation with Text, Image, and Audio Inputs Solving Quantitative Reasoning Problems with Language Models

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-10T04:31:01.954955Z digest=sha256:4023bbaea8e5fdbb6b0b6da9b939537487897beed4e23687bcab78af1eea969f

Observation 49784fcb-ff62-447b-ae82-073fde45b482 · inbound

Fine-Tuning Small Reasoning Models for Quantum Field Theory cites this paper.

Fine-Tuning Small Reasoning Models for Quantum Field Theory Solving Quantitative Reasoning Problems with Language Models

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T03:23:18.770963Z digest=sha256:485aeb870f7ae9e555ed0b8f112cec498abb1b2c702a5f8540d9225557c0378b

Observation efd631ab-6fa7-4f5d-92c3-9a19682e306a · inbound

Math Takes Two: A test for emergent mathematical reasoning in communication cites this paper.

Math Takes Two: A test for emergent mathematical reasoning in communication Solving Quantitative Reasoning Problems with Language Models

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-14T22:08:04.270133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-14T22:05:13.243174Z digest=sha256:e3b4d0a7cd1855298b6c9c63a4a08b210af173f35d53c69004875685b1f111ce

Observation feab345a-50ce-4ca3-88cd-27cafeaeb9e7 · inbound

Co-Evolving Policy Distillation cites this paper.

Co-Evolving Policy Distillation Solving Quantitative Reasoning Problems with Language Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-07T08:23:41.819485Z digest=sha256:7574b26b0b6345b02b036394a35622ab5655ae0878791a74610f81391b397cf9

Observation af0cf941-b532-4d8c-afeb-c3c16f2f100d · inbound

Diversity in Large Language Models under Supervised Fine-Tuning cites this paper.

Diversity in Large Language Models under Supervised Fine-Tuning Solving Quantitative Reasoning Problems with Language Models

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-09T20:32:37.788283Z digest=sha256:71ac31d5b3dfe4df8a68de8a7e899aed468bf06ce4b9e54d5821131c7fb72a77

Observation ad1e6bf7-cfe6-4dd0-92e8-2d201e745fb7 · inbound

Diversity in Large Language Models under Supervised Fine-Tuning cites this paper.

Diversity in Large Language Models under Supervised Fine-Tuning Solving Quantitative Reasoning Problems with Language Models

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-12T03:10:22.314719Z digest=sha256:5fbebbf30252dd1f97ac098be72cf6d4650c597881054045118fff52f3b311d8

Observation ab27407c-c671-4305-986c-f5f44e43a829 · inbound

Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO cites this paper.

Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO Solving Quantitative Reasoning Problems with Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T14:53:35.133157Z digest=sha256:a8bc2323f8b84fd4c9eaed1e730d3e19d3f93861013cf12920d2f1bebdc78bb8

Observation b2894fe1-54b8-4344-935a-6eee4cce34ff · inbound

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key Solving Quantitative Reasoning Problems with Language Models

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-08T09:35:47.501360Z digest=sha256:625a3436d45fe596b8425c388e4fd6c07ad9b7cab3ca3e9f855e47efb4a33fa0

Observation 1a4ae588-c66f-4b5f-824d-a8240fc46519 · inbound

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key Solving Quantitative Reasoning Problems with Language Models

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-12T03:16:59.195706Z digest=sha256:5d5b381e7f190aab992f3dd6883aac17eb949531e79e03f34fa3dd0ed771e2d8

Observation ea95de36-787d-47b4-ba87-9ca6aa6f2eb9 · inbound

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key Solving Quantitative Reasoning Problems with Language Models

Reference 81

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:39:10.574860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-20T22:36:13.781114Z digest=sha256:061ed943a3e44fe3c0835bc69d74337e361ace49e580c8276a21d5a04f4a7521

Observation 4a6c09a5-9517-48d3-97c6-d75c04a08688 · inbound

AI co-mathematician: Accelerating mathematicians with agentic AI cites this paper.

AI co-mathematician: Accelerating mathematicians with agentic AI Solving Quantitative Reasoning Problems with Language Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-08T09:31:55.315364Z digest=sha256:7920264a8171bc7425573d39aef34d18e2d2a7ea316b1015ac9791a0abbdaa3d

Observation b67b3cc6-1079-470d-9afc-cd757714e417 · inbound

AI co-mathematician: Accelerating mathematicians with agentic AI cites this paper.

AI co-mathematician: Accelerating mathematicians with agentic AI Solving Quantitative Reasoning Problems with Language Models

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-14T21:19:28.656582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-14T21:04:57.852889Z digest=sha256:6cfe8e4ec7aaab41330902d6f6ad2a79ca93bf4ef759e162fb96b07341dc98f0

Observation 67a8ea0a-2f08-42c3-a7b4-49fd54de8e05 · inbound

Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models cites this paper.

Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-11T02:02:41.411795Z digest=sha256:299d946a453aa6d465dadd280fc4ad9d0faf4c92168d472e4909dab3e0efbbe6

Observation 80e57765-08e0-454d-990a-3c5d3197e885 · inbound

KL for a KL: On-Policy Distillation with Control Variate Baseline cites this paper.

KL for a KL: On-Policy Distillation with Control Variate Baseline Solving Quantitative Reasoning Problems with Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-12T22:43:59.458883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-11T03:31:07.462474Z digest=sha256:43055d2c94bcdb160abfc8f549e62d260204738836d29f77e3ed476c89d222f0

Observation 2cc75565-6293-4305-a0ad-b9802c21183b · inbound

Rotation-Preserving Supervised Fine-Tuning cites this paper.

Rotation-Preserving Supervised Fine-Tuning Solving Quantitative Reasoning Problems with Language Models

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-05-13T06:27:24.455152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-13T06:26:20.393476Z digest=sha256:684305744296fe75206c0c7760cc202e726391710ff2908d61c7d818a4af635c

Observation 9070d867-ae15-435c-97db-5dcb908e3d29 · inbound

Teacher-Guided Policy Optimization for On-Policy Reasoning Distillation under Large Policy Divergence cites this paper.

Teacher-Guided Policy Optimization for On-Policy Reasoning Distillation under Large Policy Divergence Solving Quantitative Reasoning Problems with Language Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-14T20:12:54.682473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-14T20:12:32.638453Z digest=sha256:317887ae1516f808b88ddf219c739cca0a824fe549a5fde2edd924921a2f0624

Observation dcc48307-2e9a-4ace-85de-55be68ee9c9a · inbound

LLMs Know When They Know, but Do Not Act on It: A Metacognitive Harness for Test-time Scaling cites this paper.

LLMs Know When They Know, but Do Not Act on It: A Metacognitive Harness for Test-time Scaling Solving Quantitative Reasoning Problems with Language Models

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-15T04:49:43.867923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-15T04:49:20.837352Z digest=sha256:76d179d56f630204aad2f1f471aec1995ee74a5e786f985c1b88341fab79c2bd

Observation 509986d1-fd53-4415-a0cc-9bdf711ab8b5 · inbound

AGPO: Adaptive Group Policy Optimization with Dual Statistical Feedback cites this paper.

AGPO: Adaptive Group Policy Optimization with Dual Statistical Feedback Solving Quantitative Reasoning Problems with Language Models

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-05-21T07:14:02.376568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T07:11:13.499763Z digest=sha256:dee28c8418aa3bfd41365e0a7b077a6985fa90b3bff4a8ad1e638a536e89b8da

Observation bc2750ca-96c5-4296-9f70-71c7bc2deda3 · inbound

Intelligence as Managed Autonomy: Failure, Escalation, and Governance for Agentic AI Systems cites this paper.

Intelligence as Managed Autonomy: Failure, Escalation, and Governance for Agentic AI Systems Solving Quantitative Reasoning Problems with Language Models

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-06-29T16:53:41.384829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-29T16:45:06.928400Z digest=sha256:6a651279a942ae7f239e1369241e1df7a214d9136ac662b15135ecb8638ed36c

Observation c86be0a4-b388-4e13-844a-acabc39fad4c · inbound

CAST: Non-Privileged Clipped Asymmetric Self-Teaching with Advantage Flipping for GRPO cites this paper.

CAST: Non-Privileged Clipped Asymmetric Self-Teaching with Advantage Flipping for GRPO Solving Quantitative Reasoning Problems with Language Models

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-07-01T19:26:01.039451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T22:25:04.067339Z digest=sha256:5ed20fd6301ff8d3fcc4f990e427699935e2742f1a8047f0a0b5b92229e23dee

Observation 32f183b1-3da3-49b7-9b7a-b02d827442b5 · inbound

Off-the-Shelf LLMs as Process Scorers: Training-Free Alternative to PRMs for Mathematical Reasoning cites this paper.

Off-the-Shelf LLMs as Process Scorers: Training-Free Alternative to PRMs for Mathematical Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-07-01T22:36:17.516396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-28T15:13:59.803306Z digest=sha256:3f1214760e0677dae16914bf7b22a5c466dadfbbdefa0652b6c2ab08ea587a57

Observation 8bf72e2a-1783-43c6-9d8a-dea516975245 · inbound

Evaluating Reasoning Fidelity in Visual Text Generation cites this paper.

Evaluating Reasoning Fidelity in Visual Text Generation Solving Quantitative Reasoning Problems with Language Models

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-02T07:16:44.542613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T07:03:38.967856Z digest=sha256:c1e2ca42580de14a98154783f50e44d00d7b74ddf37c90033b8ef9432f877611

Observation 9a8dcf91-01b6-47ef-a8db-cc7c2df2d7b3 · inbound

RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning cites this paper.

RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning Solving Quantitative Reasoning Problems with Language Models

Reference 9

Resolution
metadata mismatch
local_arxiv, observed 2026-06-27T22:31:21.110435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-27T22:25:52.959859Z digest=sha256:625444a009b4979ac6d3ef75e6cb5759cc057e59f53000a29c8b8b7d7944f8f5

Observation dca2582a-0a01-401a-870b-f1a93f8443a0 · inbound

Investigating LLM's Problem Solving Capability -- a Study on Statics Questions cites this paper.

Investigating LLM's Problem Solving Capability -- a Study on Statics Questions Solving Quantitative Reasoning Problems with Language Models

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-07-01T08:25:33.407001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-01T08:18:19.972971Z digest=sha256:9282e9f6acd9d822dca06c94e2a57d74257cca10fff58c421d466a53ac72a44e

Observation c8716189-2874-4206-8d3d-81b5277bf5fa · inbound

Post-Training Shifts Confidence: A Three-Stage Analysis of How SFT, RL, and OPD Shape CoT Calibration cites this paper.

Post-Training Shifts Confidence: A Three-Stage Analysis of How SFT, RL, and OPD Shape CoT Calibration Solving Quantitative Reasoning Problems with Language Models

Reference 92

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no resolver link, observed 2026-08-02T03:56:24.673658Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T03:56:24.673658Z digest=sha256:08f4dfab095e83dc9226287d443e8964fd7c95b2c999141a765b4fa8f3461322

Observation 016a574d-6436-42a8-906d-21d3677f916c · inbound

Making Open-Source Text LLM Watermarks Durable Against Merging cites this paper.

Making Open-Source Text LLM Watermarks Durable Against Merging Solving Quantitative Reasoning Problems with Language Models

Reference 41

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unresolved
no resolver link, observed 2026-08-02T14:26:15.074953Z

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source=pdf_text observed=2026-08-02T14:26:15.074953Z digest=sha256:6790ea5cba5dfd09ac99a4ee155516da188d7ed42a7632f0eda446a206f7a9bb

Observation 82427e8f-5477-45f9-bfa7-e47d48933bd8 · inbound

Learning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning cites this paper.

Learning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning Solving Quantitative Reasoning Problems with Language Models

Reference 16

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unresolved
no resolver link, observed 2026-08-01T06:14:26.859099Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:14:26.859099Z digest=sha256:a9f549d462cc3c68b27ed571270962c98eafa97b3cf4ce4544a8a0b557f9de24

Observation 3ce70b83-5571-43e0-9412-66e1828d9c37 · inbound

(Towards) Scalable Reliable Automated Evaluation with Large Language Models cites this paper.

(Towards) Scalable Reliable Automated Evaluation with Large Language Models Solving Quantitative Reasoning Problems with Language Models

Reference 34

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no resolver link, observed 2026-07-31T12:20:07.003081Z

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source=arxiv_source observed=2026-07-31T12:20:07.003081Z digest=sha256:0ffaec49ba22acb2e4b4b30aff019687e24b00bccea3defd4d92db670f684cab

Observation 62507b1a-98bb-452b-bf33-54dc3613156e · inbound

When Teachers Mislead: Spurious-Signal-Aware On-Policy Distillation cites this paper.

When Teachers Mislead: Spurious-Signal-Aware On-Policy Distillation Solving Quantitative Reasoning Problems with Language Models

Reference 2022

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unresolved
no resolver link, observed 2026-08-05T15:45:28.124748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:45:28.124748Z digest=sha256:92949ab202c9e88b7e65b1822448b8348e615886916e354eeafc51c720ad38a1