Paper Citation Record · LEDGER

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2505.24823.

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

pith.paper-citation-record.v1
2505.24823 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:22:26.217604Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

verified exact0
verified fuzzy9
unresolved36
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b5a48d0e-96b2-47ab-837b-9a9a873b4ed1 · outbound

This paper cites A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:22.263718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 808a5c32-b05e-48b9-99ca-4c0c0033234a · outbound

This paper cites Romera-Paredes, M.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Romera-Paredes, M

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:22.403429Z

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Observation fe59b0df-1003-4619-bb2e-5994d0365be5 · outbound

This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:22.541012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df50c6f1-8be3-4d9d-915d-7c18ab264605 · outbound

This paper cites Llm-sr: Scientific equation discovery via programming with large language models,.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Llm-sr: Scientific equation discovery via programming with large language models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:28.507274Z

Source-reported events for the cited work

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

Observation a364e9d4-33f0-4d5c-93a0-a456a9d46440 · outbound

This paper cites Brenner, and Eun-Ah Kim.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Brenner, and Eun-Ah Kim

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:22.854654Z

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Observation 51298dbc-c492-4a51-8376-bb4d517b523d · outbound

This paper cites LLM-Feynman: Leveraging Large Language Models for Universal Scientific Formula and Theory Discovery.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models LLM-Feynman: Leveraging Large Language Models for Universal Scientific Formula and Theory Discovery

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:22.956783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32b624ba-dac3-4396-a211-711b3a7bd2a1 · outbound

This paper cites Large physics models: Towards a collaborative approach with large language models and foundation models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Large physics models: Towards a collaborative approach with large language models and foundation models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.042992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4563436-9104-4f8f-87b4-a07a5a2783fb · outbound

This paper cites Advancing AI-Scientist Understanding: Multi-Agent LLMs with Interpretable Physics Reasoning.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Advancing AI-Scientist Understanding: Multi-Agent LLMs with Interpretable Physics Reasoning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.142195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b2493fa-4321-4818-a7ef-0128d76ea2ca · outbound

This paper cites Gemini Robotics: Bringing AI into the Physical World.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Gemini Robotics: Bringing AI into the Physical World

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.253023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 396fc029-6d63-4220-a6ad-614e4ce1b101 · outbound

This paper cites Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.366842Z

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Unavailable: canonical work link unavailable.

Observation 3f783fd1-951f-41cb-9688-782fa1291086 · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.478351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 803b530e-0457-400d-a200-728c2ce4442f · outbound

This paper cites Expert and novice performance in solving physics problems.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Expert and novice performance in solving physics problems

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:28.365459Z

Source-reported events for the cited work

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

Observation 9371a1df-69bf-44c3-85d2-988571c33163 · outbound

This paper cites an unresolved cited work.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.661672Z

Source-reported events for the cited work

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Observation f7c2d1ae-54f7-48bf-9368-62c51f1b0030 · outbound

This paper cites Cognitive load during problem solving: Effects on learning.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Cognitive load during problem solving: Effects on learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.740680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b35877a-f8ac-416f-aebc-eba31f4ffe22 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.833827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 521599b2-9065-4a7f-931a-2bbcfdfd0ee4 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Measuring Massive Multitask Language Understanding

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.924503Z

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Observation dbb57740-cea8-471f-bcbf-fc7a73709532 · outbound

This paper cites IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:23.996077Z

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Unavailable: canonical work link unavailable.

Observation f4e69425-a990-4618-bc0a-e1b6462b638a · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.060193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdf12970-07b3-43f0-bc47-85ff7762fa00 · outbound

This paper cites AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.129251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79cc130c-bbb1-43d2-b840-5dcaa3d9d231 · outbound

This paper cites Have LLMs advanced enough? a chal- lenging problem solving benchmark for large language models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Have LLMs advanced enough? a chal- lenging problem solving benchmark for large language models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.207587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02dda92c-2780-45b9-8f2c-1f865cb1b5ae · outbound

This paper cites SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.297967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c387862-5d82-4e16-9e86-65313924be74 · outbound

This paper cites Mmlu-pro: A more robust and challenging multi-task language understanding benchmark.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Mmlu-pro: A more robust and challenging multi-task language understanding benchmark

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.372229Z

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Unavailable: canonical work link unavailable.

Observation a869ab84-d082-48b6-ba44-90cd9788c3f8 · outbound

This paper cites Scieval: A multi-level large language model evaluation benchmark for scientific research.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Scieval: A multi-level large language model evaluation benchmark for scientific research

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:28.130295Z

Source-reported events for the cited work

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

Observation 5a431d61-daf8-4a7e-897a-e5c964430a73 · outbound

This paper cites TheoremQA: A Theorem-driven Question Answering dataset.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models TheoremQA: A Theorem-driven Question Answering dataset

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.562397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af06dde0-a12c-42a3-ade6-77517c781a61 · outbound

This paper cites Humanity's Last Exam.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Humanity's Last Exam

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.630990Z

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Unavailable: canonical work link unavailable.

Observation 4a96a0a4-9d2a-495f-b9bc-2f049d547835 · outbound

This paper cites OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.704748Z

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Observation 180c217d-8b14-420f-b85d-f8106afa1290 · outbound

This paper cites Olympicarena: Benchmarking multi-discipline cognitive reasoning for superintelligent ai.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Olympicarena: Benchmarking multi-discipline cognitive reasoning for superintelligent ai

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.776896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b4783e0-6f33-4c67-a1ba-a05baec08497 · outbound

This paper cites Using Large Language Model to Solve and Explain Physics Word Problems Approaching Human Level.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Using Large Language Model to Solve and Explain Physics Word Problems Approaching Human Level

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.850334Z

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Unavailable: canonical work link unavailable.

Observation 03c59c30-0f57-4c2b-9221-927d494fe54b · outbound

This paper cites UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:24.926698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1401a96-4fdf-4fce-8ad7-6f18ae4f77ba · outbound

This paper cites PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.013730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa447c21-1001-482c-9c3f-e2f2bc2942c1 · outbound

This paper cites PhysReason: A Comprehensive Benchmark towards Physics-Based Reasoning.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models PhysReason: A Comprehensive Benchmark towards Physics-Based Reasoning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.112064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9993ea64-1444-49b2-b6e0-7d4512665de9 · outbound

This paper cites CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.206982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18e58079-ba3c-4c38-ab28-ba13d822cc40 · outbound

This paper cites Mm-phyqa: Multimodal physics question-answering with multi-image cot prompting.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Mm-phyqa: Multimodal physics question-answering with multi-image cot prompting

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.273400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6da479d7-7839-4893-9e43-1d28264fe77c · outbound

This paper cites FEABench: Evaluating Language Models on Multiphysics Reasoning Ability.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models FEABench: Evaluating Language Models on Multiphysics Reasoning Ability

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.362149Z

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Unavailable: canonical work link unavailable.

Observation 7a961bc9-1382-43b1-9101-ff2fc5c1d320 · outbound

This paper cites Learning to reason with llms, September 2024.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Learning to reason with llms, September 2024

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:27.886863Z

Source-reported events for the cited work

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

Observation f3766474-28fc-4d52-aaee-35044a14fcff · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.520633Z

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Unavailable: canonical work link unavailable.

Observation 82d86910-6508-4c19-a1ed-f374995122c0 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.610427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df088cbf-23f6-4b89-ad03-62d780ba7c78 · outbound

This paper cites Claude 3.7 sonnet and extended thinking mode.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Claude 3.7 sonnet and extended thinking mode

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:27.712882Z

Source-reported events for the cited work

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

Observation 9c98da01-6cb7-4932-8275-2d57c4e85b04 · outbound

This paper cites Qwq: Reflect deeply on the boundaries of the unknown, November 2024.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Qwq: Reflect deeply on the boundaries of the unknown, November 2024

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:27.536957Z

Source-reported events for the cited work

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

Observation 610037b8-ea61-4d33-9e03-36693ba95cde · outbound

This paper cites Openai o3 and o4-mini system card.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Openai o3 and o4-mini system card

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:27.353683Z

Source-reported events for the cited work

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

Observation bc3d9c65-2030-4145-a99d-14949198f77d · outbound

This paper cites URL https://blog.google/technology/ google-deepmind/gemini-model-thinking-updates-march-2025/.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models URL https://blog.google/technology/ google-deepmind/gemini-model-thinking-updates-march-2025/

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:27.190613Z

Source-reported events for the cited work

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

Observation 0c3101cb-d4ed-4803-9e0f-7821cf0c4c4f · outbound

This paper cites Introducing gpt-4.1 in the api, April 2025.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Introducing gpt-4.1 in the api, April 2025

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:25.980401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41e85d35-4d36-4afa-9448-d6f018c2cc8d · outbound

This paper cites Claude 3.7 sonnet and claude code, February 2025.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Claude 3.7 sonnet and claude code, February 2025

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:22:27.046469Z

Source-reported events for the cited work

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

Observation 2d41297a-7b22-48f6-824a-25225da34672 · outbound

This paper cites Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:26.127078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56ffc97e-5c6e-4606-9adb-ba5a36adf4f6 · outbound

This paper cites DeepSeek-V3 Technical Report.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models DeepSeek-V3 Technical Report

Reference 46

Resolution: malformed identifier; no resolver link, observed 2026-08-07T12:22:26.217604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e7d5fea-6140-40d0-9f66-44aae2f38c47 · outbound

This paper cites LLM-SR: Scientific Equation Discovery via Programming with Large Language Models.

PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models LLM-SR: Scientific Equation Discovery via Programming with Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T12:22:22.780339Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.