Paper Citation Record · LEDGER

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 5 inbound Pith citation observations for arXiv:2505.19501.

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

pith.paper-citation-record.v1
2505.19501 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:36.509160Z

measured 55 of 55 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:36.029822Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

50 of 50 outbound references displayed

verified exact2
verified fuzzy11
unresolved37
parse uncertain0
malformed identifier0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation afea2159-1a30-42ab-b491-9dbae7c6f438 · outbound

This paper cites https://groups.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning https://groups

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:39.579019Z

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 98928a95-ae8b-49ba-95c7-d9675e3662e6 · outbound

This paper cites Publicly Available Clinical BERT Embeddings.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Publicly Available Clinical BERT Embeddings

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:32.630844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec5f7560-c4fe-4f4e-b909-30935d26a96c · outbound

This paper cites SciBERT: A Pretrained Language Model for Scientific Text.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning SciBERT: A Pretrained Language Model for Scientific Text

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:32.723398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95578303-0a4e-43f2-8890-0b52b5acb70c · outbound

This paper cites SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:32.807425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4b22f4d-898f-4f46-9fba-5bcad3ffbc6f · outbound

This paper cites MaxMin-RLHF: Alignment with Diverse Human Preferences.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning MaxMin-RLHF: Alignment with Diverse Human Preferences

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:32.906989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83a7ae87-6a9a-46b3-ac06-a3b7d5c2023c · outbound

This paper cites Deep reinforcement learning from human preferences.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Deep reinforcement learning from human preferences

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:39.374637Z

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 75646ddd-da90-4e10-8468-4bf1706831ad · outbound

This paper cites A 5′ utr language model for decoding untranslated regions of mrna and function predictions.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning A 5′ utr language model for decoding untranslated regions of mrna and function predictions

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:39.099082Z

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 1918dbac-c09e-49cf-bc17-08613e799728 · outbound

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

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:33.136460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7ef9dc2-1148-494b-bc6c-906cf4dcb15e · outbound

This paper cites Temporal consistency for llm reasoning process error identification.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Temporal consistency for llm reasoning process error identification

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-07T14:16:37.578310Z

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 3ff156e0-1d28-4814-a7ca-3c65c51b2479 · outbound

This paper cites Embodied LLM Agents Learn to Cooperate in Organized Teams.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Embodied LLM Agents Learn to Cooperate in Organized Teams

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:33.324986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64f9b7dc-1b6b-405d-833b-2162ea59247f · outbound

This paper cites Math-perturb: Benchmarking llms’ math reasoning abilities against hard perturbations.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Math-perturb: Benchmarking llms’ math reasoning abilities against hard perturbations

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.936618Z

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 24d7bf2b-47c5-4494-b0a8-a3bbcfec2ef8 · outbound

This paper cites Crispr-gpt: An llm agent for automated design of gene-editing experiments.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Crispr-gpt: An llm agent for automated design of gene-editing experiments

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.786177Z

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 ac6f6e28-6b99-4c06-a28e-2d2507c3c7ea · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning A Survey on Large Language Models for Code Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:33.563390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6eafb56-a2a7-4cfc-8e9c-54abbfa772b6 · outbound

This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning What disease does this patient have? a large-scale open domain question answering dataset from medical exams

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.645884Z

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 f33a9524-a96c-4116-884a-000a202120a4 · outbound

This paper cites PubMedQA: A Dataset for Biomedical Research Question Answering.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning PubMedQA: A Dataset for Biomedical Research Question Answering

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:33.769378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cdd6523-8ddc-4899-b1e9-b1baf5e61344 · outbound

This paper cites Bioasq-qa: A manually curated corpus for biomedical question answering.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Bioasq-qa: A manually curated corpus for biomedical question answering

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.500172Z

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 b7fa524b-9938-4b67-87b6-074d9acbade0 · outbound

This paper cites Training Language Models to Self-Correct via Reinforcement Learning.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Training Language Models to Self-Correct via Reinforcement Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:33.944484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b06293d-b9af-4ed1-ae10-8ded4e7c4f18 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.024067Z

Source-reported events for the cited work

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Observation 5a98f1ac-515c-4c98-8df5-36f402dc2723 · outbound

This paper cites LAB-Bench: Measuring Capabilities of Language Models for Biology Research.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning LAB-Bench: Measuring Capabilities of Language Models for Biology Research

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.099327Z

Source-reported events for the cited work

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Observation 77bbd0b2-17ea-4458-9a67-bf64eef549bc · outbound

This paper cites Biobert: a pre-trained biomedical language representation model for biomedical text mining.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Biobert: a pre-trained biomedical language representation model for biomedical text mining

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.189406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6a6037e-1978-4a79-95c8-48a164660ba6 · outbound

This paper cites Mapping the Increasing Use of LLMs in Scientific Papers.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Mapping the Increasing Use of LLMs in Scientific Papers

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.285798Z

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Unavailable: canonical work link unavailable.

Observation 33172ea8-d605-4bde-a5d1-e304650e5cb8 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Understanding R1-Zero-Like Training: A Critical Perspective

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.365003Z

Source-reported events for the cited work

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Observation f8694ac4-f500-4491-96bc-cfff4e84cfcf · outbound

This paper cites Biogpt: generative pre-trained transformer for biomedical text generation and mining.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Biogpt: generative pre-trained transformer for biomedical text generation and mining

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.339770Z

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 61c29d7e-f8ba-48c3-9696-7523461a9b8a · outbound

This paper cites BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.525450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a9d5b13-ca7d-4bd3-86df-09cefabe942b · outbound

This paper cites Covid-qa: A question answering dataset for covid-19.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Covid-qa: A question answering dataset for covid-19

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.178198Z

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 212554fe-81aa-4ae6-826e-3be54a7976f7 · outbound

This paper cites Training language models to follow instructions with human feedback.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Training language models to follow instructions with human feedback

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:38.027226Z

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 ec343161-45bc-43cb-ba87-66f2b60092bd · outbound

This paper cites Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering

Reference 27

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Observation 77d25e6f-a006-435a-be4b-15f8fd6de7a2 · outbound

This paper cites A domain- specific next-generation large language model (llm) or chatgpt is required for biomedical engineering and research.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning A domain- specific next-generation large language model (llm) or chatgpt is required for biomedical engineering and research

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:37.871064Z

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 1153b7b9-16d3-4381-8ba0-ecd68bac0d78 · outbound

This paper cites Humanity's Last Exam.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Humanity's Last Exam

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:34.919303Z

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Unavailable: canonical work link unavailable.

Observation c6f1273f-6232-412d-8f21-579df929b853 · outbound

This paper cites SciFive: a text-to-text transformer model for biomedical literature.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning SciFive: a text-to-text transformer model for biomedical literature

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.015805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 398dcbeb-5310-4dbe-bf77-71a92d4be9d6 · outbound

This paper cites OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.092269Z

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Observation 01f58c65-b194-47b9-bdd7-73f99773a326 · outbound

This paper cites Gpqa: A graduate-level google-proof q&a benchmark.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Gpqa: A graduate-level google-proof q&a benchmark

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.171091Z

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Observation f1dbd3a9-b21d-4d71-ab50-a65683f5700f · outbound

This paper cites Proximal Policy Optimization Algorithms.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.239501Z

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Observation 53a1d2b6-08e4-4829-8fe3-83f970070603 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.320838Z

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Observation d0279c49-b79e-457c-9f38-f64049913834 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024

Reference 35

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Observation e2d81dc0-19e9-4631-953a-61b9f0b2d066 · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.431025Z

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Observation 11ccb532-811a-4fa2-a7c2-9f49545af144 · outbound

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

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Galactica: A Large Language Model for Science

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.497267Z

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Observation 00e70ae3-52f4-48ff-9b2c-d3a0eb1a415b · outbound

This paper cites A call for built-in biosecurity safeguards for generative ai tools.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning A call for built-in biosecurity safeguards for generative ai tools

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.578517Z

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Observation 5a8f5076-31cb-4081-a8a1-dd64cc10cea3 · outbound

This paper cites Math-shepherd: Verify and reinforce llms step-by-step without human annotations.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Math-shepherd: Verify and reinforce llms step-by-step without human annotations

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.641355Z

Source-reported events for the cited work

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Observation 7f645668-9c8f-4882-b23b-0fe5ee70045a · outbound

This paper cites Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.711109Z

Source-reported events for the cited work

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Observation b5447346-bd0c-432b-8df5-a6d32676b0b1 · outbound

This paper cites DARWIN Series: Domain Specific Large Language Models for Natural Science.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.778875Z

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Observation bc56ceb1-ca1e-45ab-a9e7-534e7fc3ea92 · outbound

This paper cites A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce

Reference 42

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Observation bc33c128-912a-46f2-b9d8-2183cc8c76cf · outbound

This paper cites ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.917247Z

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Observation 092e32ff-81b6-4a4c-b27c-8426ce22c4ec · outbound

This paper cites GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:35.973838Z

Source-reported events for the cited work

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Observation e54ca4a9-5f34-48a3-bb04-952e8cce4afc · outbound

This paper cites Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:36.029822Z

Source-reported events for the cited work

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Observation a53ce49d-145b-4e6a-ac43-cc76e727053d · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:36.086883Z

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Observation 82e82881-5bed-4ba4-b91c-2b451aba0c5c · outbound

This paper cites BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:16:36.808890Z

Source-reported events for the cited work

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Observation 2c79a4eb-c102-4f33-bc36-b20ffc301b21 · outbound

This paper cites A generalist vision–language foundation model for diverse biomedical tasks.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning A generalist vision–language foundation model for diverse biomedical tasks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:36.214381Z

Source-reported events for the cited work

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Observation f38840b1-f1c2-48c1-a399-4e3266f637bd · outbound

This paper cites Scientific large language models: A survey on biological & chemical domains.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning Scientific large language models: A survey on biological & chemical domains

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:36.302753Z

Source-reported events for the cited work

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Observation d3bbb883-9740-4886-bf2b-91166959f7c4 · outbound

This paper cites DPO Meets PPO: Reinforced Token Optimization for RLHF.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning DPO Meets PPO: Reinforced Token Optimization for RLHF

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:36.509160Z

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Pith citing papers

Observation e54ca4a9-5f34-48a3-bb04-952e8cce4afc · inbound