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Paper Citation Record · LEDGER

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 81 of 81 outbound references and 3 inbound Pith citation observations for arXiv:2505.24105.

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

pith.paper-citation-record.v1
2505.24105 v1

Coverage vector

measured 81 of 81 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:16.167357Z

measured 84 of 84 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:42:34.643403Z

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

81 of 81 outbound references displayed

  • verified exact1
  • verified fuzzy24
  • unresolved56
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External citation measurements

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

Outbound references

Observation 88cd335b-b05b-4e69-9ea7-8938a1be17fd · outbound

This paper cites GPT-4 Technical Report.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-07T12:40:05.748193Z digest=sha256:576e7ba037ac0fb27aa6cb380506f5204f2d594c3cba299687ffa8aebc917330

Observation d031cc18-80a3-4363-b2aa-beb9f1a67af2 · outbound

This paper cites Claude 3 haiku: our fastest model yet, March 2024.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Claude 3 haiku: our fastest model yet, March 2024

Reference 2

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source=pdf_text observed=2026-08-07T12:40:05.836155Z digest=sha256:fa61d186ec2f37fd57d1c5e4f59ce4a4eabebde3f73e425d207218328af6b65b

Observation ccb64938-c2e3-4146-adf7-1470961a05ba · outbound

This paper cites Claude 3.5 sonnet, June 2024.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Claude 3.5 sonnet, June 2024

Reference 3

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

source=pdf_text observed=2026-08-07T12:40:05.989525Z digest=sha256:1092f7d49b9fe3c82abf347a4cf4299f4ce6aae371e8d95a322337073a898436

Observation 25a76a8d-bac8-4dba-8c89-500edc05a857 · outbound

This paper cites Training a helpful and harmless assistant with reinforcement learning from human feedback, 2022.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Training a helpful and harmless assistant with reinforcement learning from human feedback, 2022

Reference 4

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source=pdf_text observed=2026-08-07T12:40:06.100300Z digest=sha256:8c709f35a621f1a94d5f4ce7ff9f8af36266a7b45a7c9384150859873ec0bdbc

Observation ccf6234e-e6e1-4535-84c1-6581ca90850e · outbound

This paper cites Rm-r1: Reward modeling as reasoning.arXiv preprint arXiv:2505.02387, 2025.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Rm-r1: Reward modeling as reasoning.arXiv preprint arXiv:2505.02387, 2025

Reference 5

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source=pdf_text observed=2026-08-07T12:40:06.195545Z digest=sha256:ab895ff3e7c361e7fe42fdd52e34d16d95cffc74474d5303313ee1bfc9dbc390

Observation 650e90de-3aa1-40ab-93d0-bd5cfd21236a · outbound

This paper cites TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records

Reference 6

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source=pdf_text observed=2026-08-07T12:40:06.323564Z digest=sha256:a89499cee8278deb41aa3a9bf25efb76e16f4131160e368ac7a3d0370356cdc1

Observation 6e6a513b-0f05-4bc0-8d0e-4c93033ec4d1 · outbound

This paper cites A new paradigm for accelerating clinical data science at stanford medicine, 2020.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning A new paradigm for accelerating clinical data science at stanford medicine, 2020

Reference 7

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

source=pdf_text observed=2026-08-07T12:40:06.481447Z digest=sha256:20a270bcf6906ed64f07e21328aed550fbd6e6da61255443cf126fd44ce9f011

Observation 326ae02a-724f-4313-8763-1e01c822d791 · outbound

This paper cites Electronic health records: then, now, and in the future.Yearbook of medical informatics, 25(S 01):S48–S61, 2016.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Electronic health records: then, now, and in the future.Yearbook of medical informatics, 25(S 01):S48–S61, 2016

Reference 8

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source=pdf_text observed=2026-08-07T12:40:06.646162Z digest=sha256:28f1bafabf62719112216e55aaf1c6488589128d975070fad4438337a9271544

Observation 20d7d28e-5b28-48fa-a794-14c19f6efdd7 · outbound

This paper cites Fleming, Alejandro Lozano, William J.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Fleming, Alejandro Lozano, William J

Reference 9

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source=pdf_text observed=2026-08-07T12:40:06.758263Z digest=sha256:188d2102fab795a5dd93cdb3e3b7622284ccdff9c9241138a366089ad2f1673e

Observation c33a26b2-608e-4b8e-b165-9dbfb4c71594 · outbound

This paper cites Metrics for multi-class classification: An overview.stat, 1050:13, 2020.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Metrics for multi-class classification: An overview.stat, 1050:13, 2020

Reference 10

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source=pdf_text observed=2026-08-07T12:40:06.880668Z digest=sha256:0f466a5a924082d94812765099cbcabd6680b846c45c3d31ee968b2f57fc5749

Observation f6f7d809-fa99-4a90-8eff-08d7f966d1db · outbound

This paper cites The Llama 3 Herd of Models.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning The Llama 3 Herd of Models

Reference 11

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source=pdf_text observed=2026-08-07T12:40:07.001760Z digest=sha256:ed8196c3d427253360f7940542a66b5e9ff20212fc0e4172b0afef496e9c274c

Observation 8e34339c-d7bc-46cd-a13f-f39629154c2d · outbound

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

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

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source=pdf_text observed=2026-08-07T12:40:07.140634Z digest=sha256:7e19d1ce7a99ada929f0011d299d8fd097e559eeea81622c1aa3e41a94c8fb70

Observation 0c5e5c1d-46c5-4dd2-8e9d-b21bbf86b506 · outbound

This paper cites Kale, Greg Ver Steeg, and Aram Galstyan.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Kale, Greg Ver Steeg, and Aram Galstyan

Reference 13

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:07.316228Z digest=sha256:2ec46a2cc91a7a798bc1bd3c3eb85b33d081f0f8ab5f565ead687ec3dc3a2624

Observation f99164e9-49d7-417a-800b-205e0852b455 · outbound

This paper cites GenCLS++: Pushing the Boundaries of Generative Classification in LLMs Through Comprehensive SFT and RL Studies Across Diverse Datasets.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning GenCLS++: Pushing the Boundaries of Generative Classification in LLMs Through Comprehensive SFT and RL Studies Across Diverse Datasets

Reference 14

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source=pdf_text observed=2026-08-07T12:40:07.437399Z digest=sha256:665e182411d6561287d014191dd08cafbf55680d1a964a9ea49d37d702c8cac5

Observation 856cf426-b842-4c7a-9ba6-3811d2568764 · outbound

This paper cites Measuring massive multitask language understanding, 2021.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Measuring massive multitask language understanding, 2021

Reference 15

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

source=pdf_text observed=2026-08-07T12:40:07.577410Z digest=sha256:ef575ed3b0230fa5d651d5a1ff5c7d405c860c259cb10c91129fc58afc644b52

Observation 1ad0381e-b8c5-4f9d-a42d-14fa07e5d01c · outbound

This paper cites DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning

Reference 16

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source=pdf_text observed=2026-08-07T12:40:07.713578Z digest=sha256:e7f486f36ddcf4f9352271e365b95e9ef8750043c185c4b53072e445a9af5777

Observation daf9734b-6cb2-4714-a051-00d83dff8885 · outbound

This paper cites Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval

Reference 17

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Observation 25ccaad0-916f-4dae-bbdd-6ece313ae861 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 18

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source=pdf_text observed=2026-08-07T12:40:07.992856Z digest=sha256:f568e4c0104d9ba3a19b557c4736d13115880e939f9ad5d4255c5f6aaccb81db

Observation 7181a258-ea6a-4c20-bbf8-aacec9d18513 · outbound

This paper cites What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Reference 19

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source=pdf_text observed=2026-08-07T12:40:08.110832Z digest=sha256:1f0e9ee4b60311a3d7233471842fad0511f92aa510dfe48403c81da07bda2362

Observation 81e95fa0-d63a-404d-b55a-74dc0d2175e0 · outbound

This paper cites Medcalc-bench: Evaluating large language models for medical calculations.Advances in Neural Information Processing Systems, 37:84730–84745, 2024.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Medcalc-bench: Evaluating large language models for medical calculations.Advances in Neural Information Processing Systems, 37:84730–84745, 2024

Reference 20

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Observation 601f646c-4f78-4781-8a0d-ba13c52e6856 · outbound

This paper cites Enhancing LLMs' Clinical Reasoning with Real-World Data from a Nationwide Sepsis Registry.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Enhancing LLMs' Clinical Reasoning with Real-World Data from a Nationwide Sepsis Registry

Reference 21

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local_arxiv, observed 2026-08-07T12:40:16.829938Z

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source=pdf_text observed=2026-08-07T12:40:08.444451Z digest=sha256:a89181e395a79cb6d4dc04cf17e84ac8db57dc5a0f788789c79781d3967bf09a

Observation 6afc9b05-c40c-40cf-896b-767efb14c6d5 · outbound

This paper cites Med-r1: Reinforce- ment learning for generalizable medical reasoning in vision-language models.arXiv preprint arXiv:2503.13939, 2025.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Med-r1: Reinforce- ment learning for generalizable medical reasoning in vision-language models.arXiv preprint arXiv:2503.13939, 2025

Reference 22

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source=pdf_text observed=2026-08-07T12:40:08.591865Z digest=sha256:c67d886ca65ebdfb94a3d0326251bc17156846282966321bdd5e9466e5294172

Observation 4e93ba54-3132-4bc9-b709-d718fdab05db · outbound

This paper cites ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model

Reference 23

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Observation 2fa7090f-a704-4064-b023-1af0552eff29 · outbound

This paper cites Rlaif vs.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Rlaif vs

Reference 24

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source=pdf_text observed=2026-08-07T12:40:08.886612Z digest=sha256:e465d992c780d590f114367a281059bd42955b6ab484a7dff7d084c82fe012ba

Observation 2975b656-7471-4252-88d4-89164de1da41 · outbound

This paper cites A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs).

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs)

Reference 25

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source=pdf_text observed=2026-08-07T12:40:09.003800Z digest=sha256:24110f51a57c8394f455610e23d5e8bd4f2882aa77b404c117f9fb8cd22f3d42

Observation 94c35891-3a53-4a1c-a2bf-6535222ead76 · outbound

This paper cites Cls-rl: Image classifica- tion with rule-based reinforcement learning.arXiv preprint arXiv:2503.16188, 2025.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Cls-rl: Image classifica- tion with rule-based reinforcement learning.arXiv preprint arXiv:2503.16188, 2025

Reference 26

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source=pdf_text observed=2026-08-07T12:40:09.163179Z digest=sha256:2677ea980221bd3d23dcaf6f47bf16ecf3a9b5c40fed7ee15c19761add1ab9d3

Observation 441e5fc8-9d7d-4e00-a28d-9e403f6397ce · outbound

This paper cites Rec-r1: Bridging generative large language mod- els and user-centric recommendation systems via reinforcement learning.arXiv preprint arXiv:2503.24289, 2025.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Rec-r1: Bridging generative large language mod- els and user-centric recommendation systems via reinforcement learning.arXiv preprint arXiv:2503.24289, 2025

Reference 27

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source=pdf_text observed=2026-08-07T12:40:09.294209Z digest=sha256:52477501701dc1598dfac321607dbca655c8580e1d4f76454d1c7be60b557ab4

Observation df6f4c4f-8547-405f-9a7c-128c6944d21e · outbound

This paper cites Panacea: A foundation model for clinical trial search, summarization, design, and recruitment.medRxiv, pages 2024–06, 2024.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Panacea: A foundation model for clinical trial search, summarization, design, and recruitment.medRxiv, pages 2024–06, 2024

Reference 28

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

source=pdf_text observed=2026-08-07T12:40:09.445067Z digest=sha256:d68d58b390de9e18f82031b99a0eb42dbf3ea7a6f4fd42c245c37d0db5333993

Observation bf925afc-28e4-41b7-8cb3-7827c2d4e9dc · outbound

This paper cites Pisces: A cross-modal contrastive learning approach to synergistic drug combination prediction.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Pisces: A cross-modal contrastive learning approach to synergistic drug combination prediction

Reference 29

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

source=pdf_text observed=2026-08-07T12:40:09.593187Z digest=sha256:9c048087102d6f8eeb27c690f73adfa51157c40852e33d2d47c88ad7a3e38d73

Observation 77f82f1d-90bb-424d-ad69-2b7662b4c4cf · outbound

This paper cites ReFT: Reasoning with Reinforced Fine-Tuning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning ReFT: Reasoning with Reinforced Fine-Tuning

Reference 30

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source=pdf_text observed=2026-08-07T12:40:09.774303Z digest=sha256:b19064213cae4757260ad6aba930df1a624bfe3f0ecc16f8bdd524fce0a110fc

Observation 747e0839-1ec3-49c4-b4f8-1e95d895c7b6 · outbound

This paper cites Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning

Reference 31

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source=pdf_text observed=2026-08-07T12:40:09.933663Z digest=sha256:9fdfeed32b6361e36a1bc6291d7e89506d933d325291a14c97d905bd9367baed

Observation 05492bca-953b-45f2-ba62-608ce5783f72 · outbound

This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning

Reference 32

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source=pdf_text observed=2026-08-07T12:40:10.057892Z digest=sha256:8dff00cd9256220e1e653a973a04274f8e89ceba1cef3daec81682a024eb0470

Observation 15441b47-519d-44f8-b74b-2f1a43c0cf99 · outbound

This paper cites Can generalist foundation models outcompete special-purpose tuning? case study in medicine.Medicine, 84(88.3):77–3, 2023.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Can generalist foundation models outcompete special-purpose tuning? case study in medicine.Medicine, 84(88.3):77–3, 2023

Reference 33

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

source=pdf_text observed=2026-08-07T12:40:10.157196Z digest=sha256:ba06ec44974488e5b1b6f67e1682ef3271cff00575597c102dd2032f831b3466

Observation d30ad90a-484b-4757-8c9b-68502463b61d · outbound

This paper cites Openai o3-mini.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Openai o3-mini

Reference 34

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

source=pdf_text observed=2026-08-07T12:40:10.270598Z digest=sha256:e478e268f7e2bd30f2f9afd877d511213f22f4ad649d99f22fb77dc37b4fde5b

Observation 4cb3e704-503c-471f-aa35-5a853328c76e · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 35

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source=pdf_text observed=2026-08-07T12:40:10.395468Z digest=sha256:7e35412f8d36f4231beea1434fc4c8ca9d9d159670c9b0ca1daa9a181dfc6ed5

Observation f1baf4f4-88fa-417e-9e9b-0245d92c04ff · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:10.512776Z digest=sha256:50a4aacecc19fde65b8d776d9ce175cbb5c9241c86d50dc1242a1b6f69956374

Observation e539073f-d59f-4e20-8372-62e44b4d1d5b · outbound

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

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering

Reference 37

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source=pdf_text observed=2026-08-07T12:40:10.620491Z digest=sha256:af741e3f428d59f32aebe746269349d0a906f35c173d40193f6cbafa87359956

Observation ea8fe538-4e8d-4330-8df7-7642bab30f10 · outbound

This paper cites MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning

Reference 38

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:10.729078Z digest=sha256:16deb14502da47ce185cbfa874848ac1ff1c03f20e73ab612f84071b339aa917

Observation a5658105-bbc9-4f79-9842-5336daec8d31 · outbound

This paper cites LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Reference 39

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source=pdf_text observed=2026-08-07T12:40:10.817997Z digest=sha256:40ddef29608518dd58d14051918d155b2063d94a1c91239a121b882350e2e6f6

Observation a6d1740c-1ff0-4826-a24e-ffe0f51b25dc · outbound

This paper cites Open-Medical-R1: How to Choose Data for RLVR Training at Medicine Domain.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Open-Medical-R1: How to Choose Data for RLVR Training at Medicine Domain

Reference 40

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source=pdf_text observed=2026-08-07T12:40:10.939828Z digest=sha256:06b9af3fcce5a743c314a23682014f838c95f7010d7140e06c60438ac77d5364

Observation 89a6aaa2-52c3-446e-bdf2-aba93ce4177a · outbound

This paper cites Manning, and Chelsea Finn.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Manning, and Chelsea Finn

Reference 41

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source=pdf_text observed=2026-08-07T12:40:11.066282Z digest=sha256:3db08cb7380a3b8cb72f33c95afc1aa9902d37b71f587cb7272ee9ff43b460f5

Observation 41a07926-025e-42f1-ac89-d8f46f86f932 · outbound

This paper cites Overview of the trec 2021 clinical trials track.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Overview of the trec 2021 clinical trials track

Reference 42

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raw_fallback, observed 2026-08-07T12:40:22.244817Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:11.129702Z digest=sha256:6ebf491ef4220523b36e46b681b48f43e16038af1a454a560cf90d7f573a1eaf

Observation ef5a72be-b684-48ee-bdcb-77fea2b15e24 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 43

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:40:11.264725Z digest=sha256:151460a6d73e9bb836faf2b49555538b45c6c178c50d25fc6adae30b3a0bcd22

Observation 696f8fb7-b375-40b8-9f4d-88b6a322a84b · outbound

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

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 44

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no resolver link, observed 2026-08-07T12:40:11.414091Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:40:11.414091Z digest=sha256:a14b85f22ed048e472db928044378c8848063d7e7f267f0ee73f6b06a87d29e0

Observation cdcc5a0b-5908-41c5-bf23-98b54e24d8f8 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning HybridFlow: A Flexible and Efficient RLHF Framework

Reference 45

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no resolver link, observed 2026-08-07T12:40:11.531409Z

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source=pdf_text observed=2026-08-07T12:40:11.531409Z digest=sha256:f8c0dbcd9e3bc7879304ec607af61834ec620933178196eadf7e6fb88458e94d

Observation 54a5c2ea-eec3-4fa9-9a1d-cce29d0c827d · outbound

This paper cites Large language models encode clinical knowledge.Nature, 620(7972):172–180, 2023.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Large language models encode clinical knowledge.Nature, 620(7972):172–180, 2023

Reference 46

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source=pdf_text observed=2026-08-07T12:40:11.665979Z digest=sha256:8344494633562a6149f24c56f23924793f0200dcd34bb8260813b7030cae58ec

Observation 7a7dded0-d419-47c2-9967-0ad3bdb0274f · outbound

This paper cites Toward expert-level medical question answering with large language models.Nature Medicine, pages 1–8, 2025.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Toward expert-level medical question answering with large language models.Nature Medicine, pages 1–8, 2025

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-07T12:40:22.139607Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:11.804203Z digest=sha256:31a6a4e4abcec32b63679d1368f4f5965fd3a7d0debfe9a1e6f0c2ed27aa235a

Observation 8e4dc3a9-b1cb-43b2-bfe1-a9e3461b421e · outbound

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

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 48

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:11.914141Z digest=sha256:ef88b78fa7ee3e07867bd98f9a4a266a56c74a1f1089d101adf6ef72efa222e9

Observation cd557f50-9eff-4477-9534-8923451c3e2e · outbound

This paper cites GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning

Reference 49

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source=pdf_text observed=2026-08-07T12:40:12.027646Z digest=sha256:94402c7ad8c9b42ad49c2bc6c4843d06c9b4cf60611b606c701dae869435ce90

Observation 645593a1-35a9-47e3-9965-95a705d71bbf · outbound

This paper cites Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across Diverse Domains.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across Diverse Domains

Reference 50

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source=pdf_text observed=2026-08-07T12:40:12.121976Z digest=sha256:1a60d0ee8a25d235bd3115edff98406ffc49e4bfdc422977686490b707f3ed5f

Observation 72ca7834-9d41-4ad0-9926-1b3fb3afe746 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 51

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no resolver link, observed 2026-08-07T12:40:12.244157Z

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source=pdf_text observed=2026-08-07T12:40:12.244157Z digest=sha256:de17714d54f9b0854f91258844bdce44acbaf61fe6791b451374a6fa5cb4591d

Observation 13ca0bb1-7e27-4cd9-a282-2bb9402481cf · outbound

This paper cites Yet another ICU benchmark: A flexible multi-center framework for clinical ML.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Yet another ICU benchmark: A flexible multi-center framework for clinical ML

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:21.914155Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:12.354142Z digest=sha256:2d59ec63468a5b8291616cf6f197f7af857c141dc40f48f816d1c64d5b5a5223

Observation c12f8d70-63dd-4ca7-adbe-2b50f4f32d0b · outbound

This paper cites Drg-llama: tuning llama model to predict diagnosis-related group for hospitalized patients.npj Digital Medicine, 7(1):16, 2024.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Drg-llama: tuning llama model to predict diagnosis-related group for hospitalized patients.npj Digital Medicine, 7(1):16, 2024

Reference 53

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raw_fallback, observed 2026-08-07T12:40:21.641415Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:12.471664Z digest=sha256:d06600d427ed8e3817b6acd21c4f06cc57fd9a73321aa24f9e579ff65da24300

Observation 9a51b7fa-1c5c-49d7-92f2-0c1a3ea56ff4 · outbound

This paper cites Reinforcement Learning for Reasoning in Large Language Models with One Training Example.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Reference 54

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source=pdf_text observed=2026-08-07T12:40:12.554505Z digest=sha256:e6816f22c487f4ad2683dfab8facd3aaf0ca0f6e6d434c03df70345d35cfe156

Observation c1ddffc4-6a31-42d1-9fad-801d8cd29507 · outbound

This paper cites Ehrshot: An ehr benchmark for few-shot evaluation of foundation models.Advances in Neural Information Processing Systems, 36:67125–67137, 2023.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Ehrshot: An ehr benchmark for few-shot evaluation of foundation models.Advances in Neural Information Processing Systems, 36:67125–67137, 2023

Reference 55

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source=pdf_text observed=2026-08-07T12:40:12.648627Z digest=sha256:60d94a9dbac98b97cbbe11cccd9e793092c829ddcd803f752f9ef3368ab82994

Observation a76b5e70-0439-4c0a-aa4e-d73a821e1bfa · outbound

This paper cites The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs

Reference 56

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no resolver link, observed 2026-08-07T12:40:12.766149Z

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source=pdf_text observed=2026-08-07T12:40:12.766149Z digest=sha256:68772960050b02b97708bcf4af1b282bc87f36dfed0f8cb3bb6a2f298be2c5d1

Observation 15631cde-5f52-4257-aac4-7dd590444ca3 · outbound

This paper cites PathVLM-R1: A Reinforcement Learning-Driven Reasoning Model for Pathology Visual-Language Tasks.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning PathVLM-R1: A Reinforcement Learning-Driven Reasoning Model for Pathology Visual-Language Tasks

Reference 57

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source=pdf_text observed=2026-08-07T12:40:12.932030Z digest=sha256:9e3d9af24f81efb465acb8d07d6493c6d142ae15f09844f29379142fe103c549

Observation b08205ac-ba61-43a9-a7d5-dbcb2efed3b2 · outbound

This paper cites Sailing by the Stars: A Survey on Reward Models and Learning Strategies for Learning from Rewards.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Sailing by the Stars: A Survey on Reward Models and Learning Strategies for Learning from Rewards

Reference 58

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no resolver link, observed 2026-08-07T12:40:13.070016Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:13.070016Z digest=sha256:c202a9d3453739999abd92d8d4020ebdbb92aef88aebe5d11d9dc52997f1dad3

Observation e5edff52-49fb-4c3a-87aa-6758030fa9da · outbound

This paper cites Instruction tuning large language models to understand electronic health records.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Instruction tuning large language models to understand electronic health records

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:21.445973Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:13.220372Z digest=sha256:29b28c05e2f06c9d5a5137c2eec639d2f1b20bb2e85c86b4f2b67f9a2c1a5447

Observation 0f342469-489a-4218-8dc4-7051792f570d · outbound

This paper cites Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning

Reference 60

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source=pdf_text observed=2026-08-07T12:40:13.347732Z digest=sha256:dca683d865a61c17c149168f9fdd19c86ed99acf0b1ef20ac8c7f9f8d9748c4b

Observation 84b1490f-7a21-4bb0-a6b9-faf8d27154c5 · outbound

This paper cites Qwen3 technical report, 2025.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Qwen3 technical report, 2025

Reference 61

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verified fuzzy
raw_fallback, observed 2026-08-07T12:40:21.277106Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:13.455171Z digest=sha256:59c7190ec7330697781655610a0f7f3875fe2d64e68e35d9f7d6383167602e45

Observation 9c2a96cf-38b2-41b9-9ea6-59fc39a26ca3 · outbound

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

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 62

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source=pdf_text observed=2026-08-07T12:40:13.610491Z digest=sha256:a7c18a03357d52ed5350f5329fb976b4634f42e06844d5da67c97e90024daab5

Observation c42987b4-5995-4040-8344-5dd7c2152bac · outbound

This paper cites Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning

Reference 63

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no resolver link, observed 2026-08-07T12:40:13.760606Z

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source=pdf_text observed=2026-08-07T12:40:13.760606Z digest=sha256:d992d53486c719efe1f532cc0c38e9bf69a1df1431007571491229015753644a

Observation 2f092779-c71c-4252-97c3-7069f5184840 · outbound

This paper cites Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning

Reference 64

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no resolver link, observed 2026-08-07T12:40:13.873620Z

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source=pdf_text observed=2026-08-07T12:40:13.873620Z digest=sha256:8047423908b428b91aa03d2979cf11c9000d19063865a4df4a1eac06fec36fe1

Observation 2c36a95e-4922-4f60-ac37-678ff6b83b2e · outbound

This paper cites Details are provided in Section F.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Details are provided in Section F

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-07T12:40:21.135687Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.010225Z digest=sha256:7f16612e683ddaff51c1d85f9e84146a5bdadc2cf059358ab2a2e04633866d57

Observation b3e4d5c4-aeb4-4a14-ae2a-36027c04532f · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 66

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unresolved
raw_fallback, observed 2026-08-07T12:40:21.008685Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.133635Z digest=sha256:011ecd033b2a4a8fc8bf7e133c431deee6402889742b3807fcf682707b4a775d

Observation 89263a09-dd93-48a7-9451-70723d27474b · outbound

This paper cites See Section F.3.4.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning See Section F.3.4

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-07T12:40:20.770263Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.231461Z digest=sha256:2e9b054621702db9d284614e7df795fda01cf36901ed60731838d959459a0ee9

Observation 7f6da25b-063a-4bec-bcc1-748d665d2a26 · outbound

This paper cites Given a dose of Drug A, what is the equivalent dose of Drug B?.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Given a dose of Drug A, what is the equivalent dose of Drug B?

Reference 68

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verified fuzzy
raw_fallback, observed 2026-08-07T12:40:20.562596Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.373677Z digest=sha256:472d92718671a8b5d485a072015f264e43e57e9ec1ac52ee06a699794b14ceec

Observation 3f082de1-aab8-42ea-9684-4b33f0fe3537 · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 69

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unresolved
raw_fallback, observed 2026-08-07T12:40:20.376274Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.559299Z digest=sha256:c831dcea098991e24f3a06e918727530ac3e2b8b459eb649c79344f3bfc4616a

Observation 4180e1d6-005e-4cd2-8e52-377b263abc24 · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 70

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unresolved
raw_fallback, observed 2026-08-07T12:40:20.075209Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.725894Z digest=sha256:86baf210d8de6c4553dd9b71e9a43e5497863392d4964bf8934008da0f62e4a6

Observation 1538b0e0-2b9b-47d7-9e2e-13491bcfa142 · outbound

This paper cites Key Considerations: - Carefully **evaluate each inclusion and exclusion criterion individually**.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Key Considerations: - Carefully **evaluate each inclusion and exclusion criterion individually**

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:19.826437Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.845286Z digest=sha256:c6f58e78e798b6ae54b20c8bc618f63d45bd1e1216f0e5ba10342dcecc449680

Observation 78876dcd-e8c1-425c-9b11-9bb14550e8ad · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:19.596276Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:14.988132Z digest=sha256:cf28ddd7944b0abaafd9fc666715b3a19a9d1e48f7b6cae71fba09390a73d685

Observation 1f7bfa90-eef2-488c-b6be-8211fe1cac03 · outbound

This paper cites The reasoning should be comprehensive, medically sound, and clearly explain how the patient’s information leads to the predicted outcome.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning The reasoning should be comprehensive, medically sound, and clearly explain how the patient’s information leads to the predicted outcome

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:19.047445Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.327917Z digest=sha256:cff0c008fa23793b30111460614488e65fcf67a395f847980abb6b6b5b7be4b4

Observation 387b5318-5e61-4ea8-83b0-442d1ce234c6 · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 75

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:18.784235Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.442336Z digest=sha256:1b06d184aa9b8a54b22aa841b143ddf31ffa632faae7ab82d970139ba7665ad1

Observation 5e44305c-dc9b-472a-a6dd-159556210ead · outbound

This paper cites Very Confident.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Very Confident

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:18.288998Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.652511Z digest=sha256:b6c087ae924bce2752978989d3627d06dc2e19be50c9e8f34c8f192ad481bd30

Observation 92b791e6-2377-437c-a8b9-e4c34729e477 · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 78

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:18.047633Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.731643Z digest=sha256:e173e1260a3b4021f3d7119aacab59b86aaf8d767cc6b4fb2a8e766f0e748a73

Observation 7b2ca135-5919-404b-be3d-7db4b0520553 · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 79

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:19.322411Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.782070Z digest=sha256:db233af687e45900171e853308d8901f455e298a5395aa5a2fc7983b0917f131

Observation 194b7b38-6e3b-4078-b552-77fe310ea1e4 · outbound

This paper cites The reasoning should be comprehensive, medically sound, and clearly explain how the patient’s information leads to the predicted outcome.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning The reasoning should be comprehensive, medically sound, and clearly explain how the patient’s information leads to the predicted outcome

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:17.796523Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.870417Z digest=sha256:bba42984d16c394a7e1d0dd8dc9dd63befaa8746e926499fa5f2cb366bcca15f

Observation 6e146c0a-7796-4a19-8648-cd5cd0d43b6b · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 81

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:17.503210Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:15.940088Z digest=sha256:24332f11b4ababa3aed33c026a83a9e817f986793f582b8289c76838e4a385ce

Observation 0b633e40-d006-4f11-9604-1435024ec891 · outbound

This paper cites an unresolved cited work.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Unresolved cited work

Reference 82

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:18.546105Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:16.057297Z digest=sha256:f8b0786b3cf076c8e083629da0708b7ae5278cc04c3817561e354c498733da22

Observation 72c93ba4-f781-4338-a665-c3c17665769b · outbound

This paper cites Very Confident.

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning Very Confident

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:17.248724Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T12:40:16.167357Z digest=sha256:c539a15cc64e2542312aa092837af01ac7b6706e4246fb73ef243494a07b032c

Pith citing papers

Observation 7e1fa655-5f32-4f99-853b-347455265ae0 · inbound

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models cites this paper.

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning

Reference 170

Resolution
unresolved
no resolver link, observed 2026-08-06T16:42:34.643403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:42:34.643403Z digest=sha256:0cc2de5626049cfdc6d42a84b074ee2a0f9d567cd47d7957ad29db5274604479

Observation 415c1475-4b7f-4c82-8317-a9fc9300d54b · inbound

Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight cites this paper.

Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-16T20:23:23.350397Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-16T20:21:40.867354Z digest=sha256:85b7e01aeffd5b42d5dd5eac8df8d1e646fd7ef557756372f48925b625d0062c

Observation 336f4c34-8c09-48f6-abde-99a5db98e613 · inbound

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments cites this paper.

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning

Reference 183

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:23:27.263072Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-15T01:20:03.181903Z digest=sha256:31ecb9a9fadd6f96ee850dac2cea79709ca8a374d642c9c3a140b6c940a09f0d