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Paper Citation Record · LEDGER

Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning

As of 20 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 2026-08-19T06:32:44.657259+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=sha256:5c53a695880d5a4cd9723e52986d56ae7fc0f61d1f9d04c7dbd8f073c7eb2c15

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:f02035e1d637f2a2c5f5ba9218aa485ad4c28a2c4a1918d7098ab857227384e8

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:05.989525Z digest=sha256:415e633aa357c924854003ef69b1aa94a2397ac26c68d5bec32e6e7449c782b0

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=sha256:01d558395e1eea456dd954c8cc8b3b53497fd8719e1b2b5262dd15ccd47b739c

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:d24fc87f44992d5cbf12e22e32fe67e37c5cea9d52bc638f0c6f8630702303f0

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:d74baeff001cc857648c7f686e03d5385075698a4ffaff950dd6d0bd99ca2a64

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:06.481447Z digest=sha256:6147ecac37ebcb2075fa764589d399dc870a129fba8e1766767e71297f1fe393

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:af24f86eda14b0fe3891f2345c318d6a531b291c2201cacaccff39a133a15ac8

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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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:06.758263Z digest=sha256:dfa1f22d199940de086689cedb5f01f25bffc5506812f04bf1f7e531fc51abdf

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:e106ce0219eba7ffc92b41b6c8afa80104c0c904733ad3d4c7cfda1672c2fa63

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=sha256:72e1e3cdc8de4bae84cd7c632667e9872ab0369924ce3c661c03bf941de0c44a

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=sha256:22268fa98aa73422daebfa85730a981683ba2aac38bf807a5eb8725c65fb5341

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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raw_fallback, observed 2026-08-07T12:40:23.408150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:07.316228Z digest=sha256:e9361dc28e03dd138960b3b37c9f1d6149cbe40b5209e14750e084316df3850c

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=sha256:1337177765016f97a600561fae42c71ba0671e7ed1520bf0cd4b7a7377f8f597

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:07.577410Z digest=sha256:34b7efad3a67cf5d12729315f357c4a62949cd774209e845666b89cf3c50d073

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=sha256:0f01a26401490370378f2cc07113bfbed0494729945fb10b777dee7a1790282a

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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source=pdf_text observed=2026-08-07T12:40:07.860220Z digest=sha256:04cbb65fd1ec42387aed041d41cb39f8dbf6d19e9682ec5c294ac4659d6452a2

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=sha256:6a56a288f6add94ae4dddb328097cce264e7e5376f686cab563a57536fc4dc59

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:c67b2dbf38d070577167ee07ef3c4ee22dbac0c097f665a83e83e15e21167f4b

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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source=pdf_text observed=2026-08-07T12:40:08.270915Z digest=sha256:600aefc96bcf7df553989009b20ec97ba82f0aa45080b78f7e395073ceb4d163

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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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:08.444451Z digest=sha256:e4cfb4004fa05640ed874a6eb7cd13dfa34367c1a81bd289bc9efb72450f3261

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=sha256:6b1611e45bae0d78b6d8a1a82d6e79333208208a2c6b11a180ea44421a2c0cc0

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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source=pdf_text observed=2026-08-07T12:40:08.713290Z digest=sha256:3c9f6d4cac3400bafa66ec664a9b411742e290d4a000482339a852572300e4d6

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:f63cdea72fb9313cddb7a8fc734600aac17f3aecee252feb26a71c2deb956e6d

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=sha256:637cdef06890e6867d23b82540b099ee1d28502700da9c81f0328fc2fe788ce1

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:fe1bbb4378b3bd6f746341170035b7f545a2aafb0e608936c88f493bbf20c744

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=sha256:67a314fd7197b6ee85be40aee477378f10d7b3ac39503d64bbd9f643bf8fc02c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:09.445067Z digest=sha256:0ca7c91daa4d266c2c75035dcbfec2072b91a38c9f9f24f2ae007e59c62ece7d

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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raw_fallback, observed 2026-08-07T12:40:22.734561Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:09.593187Z digest=sha256:925025d597bd139051dac32ef758de23dfbebd74ed8232cbf6914aec7725530b

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=sha256:0f54b820e95b3768800937f0d9a675518c8a9ec588be1b89f20fb5e3f305e728

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=sha256:35ad499996994c907deb7de731c68f98d0f9ca29a9d8c3d69e6351020d4900d2

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:a9e2a323c7c0f9a9450e12e39e4b0f281c99cb0de4f8da647c085766193697a0

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:10.157196Z digest=sha256:01f311bb25b0c4fcbc6461d371c562c54c137b0498f18214cd732221509ab23b

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:10.270598Z digest=sha256:aa161fe8d349b53f1b173296de454fe1acd74458c3bc348639d1485cda1a9b02

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=sha256:3de3805fc4dd89bbc8bd08dabd5864ec563751db75dc597dc1be2400452da4eb

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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source=pdf_text observed=2026-08-07T12:40:10.512776Z digest=sha256:8952002c68e56763e994b978638dd52de75132a20d8a00a62e6e2f6562946b18

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=sha256:915717685dc874b6895c8cc9615a1e6c7defa5234873eac5fd4300d00ea61f63

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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source=pdf_text observed=2026-08-07T12:40:10.729078Z digest=sha256:9cb2db9f4d9ceaaf170bc4383d873c3685d806693e8d3a8c7b5ee3f932b89cdf

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=sha256:2a2a51994bc12116cd76d93b1ebacadd58fc929b5ff7acec51ef1926df00eb97

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=sha256:8b49e2efde8aa119ae0f7c626a7ea77dfdbd8776b2f72caf29c71bbcae2d80b7

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=sha256:1fc0e0603801b39222880bee866348ae2bb45725af6a026e32079c492cdd048d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:11.129702Z digest=sha256:80fbbbf2c5ccb96a4493ec39bdf4b81949fbe039acb12f6fd56e18b0c1c4f9ca

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=pdf_text observed=2026-08-07T12:40:11.264725Z digest=sha256:713faad453244beb8d822afb8561c30c04586fcf6c46eef3fbc7b7b5d847e72d

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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source=pdf_text observed=2026-08-07T12:40:11.414091Z digest=sha256:9c08966432e841c11021edad229d8f4f1b645935cedda6e02ea9ff8d6f41831a

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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source=pdf_text observed=2026-08-07T12:40:11.531409Z digest=sha256:fd766b8189227168afce138312037d9863624a6a8768ff1d285df2152cfc27b2

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=sha256:3d69df223e85dd31bf3e19b2ff8570b0b80d4a77bb75adaa0229c84b321f4679

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:11.804203Z digest=sha256:eb3b8d770ceafd873aa127f717c7770858ab0b5ad7931720aac305d9ef9bbb1b

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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source=pdf_text observed=2026-08-07T12:40:11.914141Z digest=sha256:bface752471a092c2083952e166a8de499393677c94ceb06f9ea30916b99dc0b

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:da29d27a3cbd567e47ee98e114e1c904a12a1050b2bf0f8880aaf63214f4c69b

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=sha256:3ac2cc684348bac840cc778a720a2074c2485c9f8021142fd5920d7d9235b226

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=sha256:4547312b49e5e44626b327ba02feee87a102171f0dabcd294436dfa024f8c92d

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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:12.354142Z digest=sha256:2f77333182b0466b1295548f9c7d1a5332aa54cd8acdf49eddfff24100b5bef5

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:12.471664Z digest=sha256:c2f47d733fd0ef6ad5c9408bc75ea5be3c3bc90d0cd0e7438113c4c975c369e0

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:e4e37f01b6affd288cc76558afadd555f240edecd47f076fae685a923d935f88

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:f6e9190aff1d8fedc572a26677601c9c5ef98b2ff8c6a56dbe9cee3b584799ba

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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source=pdf_text observed=2026-08-07T12:40:12.766149Z digest=sha256:d338486c4a7469c95184b9e6c902f2ecfeb389131ef0c0058f4a23c3eef9836e

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=sha256:50edda94f3336ed66f9b72e260afa5dd4c7f03291c8f0a48980f691f2e244dd0

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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source=pdf_text observed=2026-08-07T12:40:13.070016Z digest=sha256:78699be5e08ceab40ac81d242af1655f8377779ad6b996e3dcb2aa889e2fd8f8

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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:13.220372Z digest=sha256:d511076b395dff0fef04b86f89c82ab3df091aa547ab309f1c434a20c613fb31

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=sha256:8c352bef80cca069feb53c351cfa786241112c3fd002464daa1c31be15910d33

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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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:13.455171Z digest=sha256:88a462360232485c2230a06778b7f547446f6997e3a295c95433c5e3b4146586

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:bee96bc8a967a3105764cbb952fe02001189b03037a0fc65dd0aa23144b00b17

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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source=pdf_text observed=2026-08-07T12:40:13.760606Z digest=sha256:b61fa88e8df8c9c8d2ac321071a813777f29f44ff0d08b51ad2e55c5ea1fe7df

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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source=pdf_text observed=2026-08-07T12:40:13.873620Z digest=sha256:2565add5340e1b30f56d09bf17726c3d319383766e622111d09a06feefd7c701

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.010225Z digest=sha256:6dfa17ba6446270bffbe66651ab6e337833a95bad1da14a9e3c0c479f693ffe2

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.133635Z digest=sha256:e8c555bbbf74ba1ec09b9040ebf3ef2d5aa74f111f38b01fe4d22fa4ad38e74f

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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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.231461Z digest=sha256:9c122bd213ce1c7e5ce5a96589f02b51e30cd75ac2cef172d7eb8d08f531c3c5

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.373677Z digest=sha256:c7ccf5edb4f59cd963af62016f9ba7d8b88424798f1d0c5e24a643ee5c18107c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.559299Z digest=sha256:2be0cfd62ea69f0fca56f01bd516257144de8699a9dc8e6047c20bb09647ad87

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.725894Z digest=sha256:f7eacd4495422a38dc221b7475945fde41852b7af099b9893c70caa25a96a1a5

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.845286Z digest=sha256:bcffac868d99a528c56ed00204838fda7c3f8a05e938f4c0ba7ec4c14afaa7fb

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:14.988132Z digest=sha256:5277d973bedac16d7140b39adfc6cc02a6ec2df97cef6e9bc7666d836a1aa071

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.327917Z digest=sha256:73c7b8aecf7873caac8b309886aa4cda19a2ddab96fcbc82bcfd3bab9dba6b36

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.442336Z digest=sha256:7e92d6d46cea0dc01bdc1eedc0a07c491d1ce4ec4e42da41af2bc6f9833a8877

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.652511Z digest=sha256:6e340eaebe2578504cd035c40490887df3b4f4518ba465e5b9cf33fac298e853

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.731643Z digest=sha256:1ec2f4324cf41a1a3cbb3a39526d1e026e38f8a583e840e3deb4975057b44425

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.782070Z digest=sha256:11695a3608d0b796eb7bd11bcf4752c949a2922a063d56ac1cfa0985bfc8eb9f

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.870417Z digest=sha256:16bb47b34898331c466ce13b7b0f125cada13395f1a3e4b732a60c2de7a6ff37

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:15.940088Z digest=sha256:8ee8658e3b85dbed3958b4245f954266e98da3744e9b56599754cc25bf3f38db

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:16.057297Z digest=sha256:89deea46355192f940f2df661839f059de61f08b55d6d29b97faf6aca0108ed5

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:40:16.167357Z digest=sha256:cb6426ae89321ceed31645cd3ebdceaee5e32812e8aa32bd21252e353f5ef931

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=sha256:0f03e27e6ab3eaca65976b75d141341850401a0d111b819d6d8f0d556f0daa3c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-16T20:21:40.867354Z digest=sha256:68a77277b4dc9c766f29ddfc8d804b2223ac5aef0cc99580d41da404e1e6573d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T01:20:03.181903Z digest=sha256:959dc2297883fa57f23d53898d4ba245002c188fe1febb1417d5e34105f2e1b5