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Paper Citation Record · LEDGER

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents

As of 18 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2608.03606.

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

pith.paper-citation-record.v1
2608.03606 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:13:32.534554Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afc4603b-355a-40c4-8a58-d983a7be7eac · outbound

This paper cites When does return-conditioned supervised learning work for offline reinforcement learning? In Advances in Neural Information Processing Systems (NeurIPS), 2022.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents When does return-conditioned supervised learning work for offline reinforcement learning? In Advances in Neural Information Processing Systems (NeurIPS), 2022

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:34.586091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:30.916113Z digest=sha256:2f8d1d9c79b05ac37f7473af1ffe2260f1a8b310847ed805fe3c5a163bc93eec

Observation 38f39604-1bfa-4b84-aa82-291ad7815dc3 · outbound

This paper cites Trialbench: Multi-modal ai-ready datasets for clinical trial prediction.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Trialbench: Multi-modal ai-ready datasets for clinical trial prediction

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:34.430927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:30.980647Z digest=sha256:f59aa1b475b1c5bcca6dfc4b390662567ad5a7d2bce0758ed56320212e9c4c46

Observation 5da2eff5-4b16-4c94-b88a-ef16e1155ff8 · outbound

This paper cites Decision transformer: Reinforcement learning via sequence modeling.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Decision transformer: Reinforcement learning via sequence modeling

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:34.246840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.080200Z digest=sha256:65a0325b4a9d18bcd145c217937a7cf088bbbae0b18fbfee1dfcfe627e64d313

Observation 1622e00c-6655-4a91-84e2-7a510dd0df6a · outbound

This paper cites RvS : What is essential for offline RL via supervised learning? In International Conference on Learning Representations (ICLR), 2022.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents RvS : What is essential for offline RL via supervised learning? In International Conference on Learning Representations (ICLR), 2022

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:34.084594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.190307Z digest=sha256:dd76284e87b04d45138c6c8e0c5e034231a07c3617d347844481faa1660090b9

Observation 579859c7-4d9c-472b-9f29-69d511b9bfc7 · outbound

This paper cites M., and Sun, J.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents M., and Sun, J

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:33.920918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.328397Z digest=sha256:88311c9e975d2b4f4f9fc63ff244dd41f135334b004a6384d0dec97c0635e7f3

Observation f59a5af0-eaa2-41da-8b69-569bb770be4a · outbound

This paper cites Biomni: A general-purpose biomedical ai agent.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Biomni: A general-purpose biomedical ai agent

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:33.765955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.425518Z digest=sha256:9be1d34448182dda333567ddb86fdfd61bc268d4b63b33eefe1f1af0f974e3d7

Observation ca1d33fd-607d-4ac2-afec-17cb1960ada6 · outbound

This paper cites Offline reinforcement learning as one big sequence modeling problem.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Offline reinforcement learning as one big sequence modeling problem

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:33.601148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.523538Z digest=sha256:b0028462151712f1a10fc908d267b3e9de4221cae99578f59f9969b86c0b2e3b

Observation b003f1de-35c9-4997-9668-436c8bb5d323 · outbound

This paper cites S., Chen, F., Gong, C., Bracken-Clarke, D., Xue, E., Yang, Y., Sun, J., and Lu, Z.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents S., Chen, F., Gong, C., Bracken-Clarke, D., Xue, E., Yang, Y., Sun, J., and Lu, Z

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:33.416324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.673635Z digest=sha256:3112ca8ce8420b7af55afb174d264250d7425091757f741940f1b0235b81dca3

Observation 6c72ebba-9545-4f59-9141-343fe579b2ea · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Offline Reinforcement Learning with Implicit Q-Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T16:13:31.791314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:13:31.791314Z digest=sha256:6bd6325bc5f5574481a90c315993bf0bf5e8d057b098f6f8c90fefb1dc5df630

Observation 944f50eb-2561-49dc-a84b-812052f33c30 · outbound

This paper cites When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning?.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T16:13:31.897892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:13:31.897892Z digest=sha256:f3a4deb1b25ddd8f7d8f0a264abd207a2f2cbe80c1afb92629b510243c2eac30

Observation 31346935-d93e-4eef-a9ee-0716b4e983db · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T16:13:31.993261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:13:31.993261Z digest=sha256:3e22f87c81a8e179687db6537002599ae0234dcd4e77a6846685b210d994460b

Observation 2c652392-baf9-4b45-99d8-a23efea3cc03 · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T16:13:32.092136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:13:32.092136Z digest=sha256:0e98ccb7b8a4fe8855fb7355df1704696bc876993001716870184e413a877588

Observation 29627c24-ad87-4a42-975e-dc0a530d7dd2 · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T16:13:32.177880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:13:32.177880Z digest=sha256:87e51279ff854f3cf23e8528fa561cf6a84b968aec4ff63a1ec7afc051cd76d6

Observation a7a2ef60-d035-4892-8844-b40f0b341648 · outbound

This paper cites F., Maximo, M.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents F., Maximo, M

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:33.263990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.262350Z digest=sha256:19fd22277a634aa11c8e281f46ab0f1d89b0c3c85571b501938c7fd8e5b5a7ff

Observation 4dd17814-fe04-48aa-955f-5411bc480670 · outbound

This paper cites AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T16:13:32.341671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:13:32.341671Z digest=sha256:3280dbae16354d4974d2d998f6bb677742b6588035c04206b8a4911946920dfd

Observation 04eae1dd-7bdd-4e88-8e1d-141492700fc3 · outbound

This paper cites and Kim, Y.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents and Kim, Y

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:33.067634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.446109Z digest=sha256:2b06495a14ed90cd1617dca0ab8e41bad5253faae66e69a89b974658e5f022e7

Observation 6b935df0-b80e-450c-81b0-cf1d5b38c049 · outbound

This paper cites T., Reed, S., Shahriari, B., Siegel, N., Merel, J., Gulcehre, C., Heess, N., and de Freitas, N.

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents T., Reed, S., Shahriari, B., Siegel, N., Merel, J., Gulcehre, C., Heess, N., and de Freitas, N

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:13:32.848904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.534554Z digest=sha256:3d864630373e27620ae1272a886eec665b700fdf246eea6575ffcff4b454689a

Pith citing papers

No inbound Pith citation observations are available.