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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:30.916113Z digest=sha256:9ab07f9ae0630ca6a3f5805ad1a76d44ea60285563cbb06cefbd4f2a09acdf85

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:30.980647Z digest=sha256:4e721ce948ae4603289ad7693d01aa1c54db26f3fb6dd6f7d3554c2dba9b39f4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.080200Z digest=sha256:498698ff8a044d5cab26ca900d0b78a5eb608698460dc55fa580b9f4ee4d6e84

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.190307Z digest=sha256:66a929bf3d9b2284203efedb2bcfafe9ad3931b2ed0ec222df251eef321d7feb

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.328397Z digest=sha256:c3af27f801ab7e4dd184024b5b95307f0f7efffd5782646006b8b90f5cc5119f

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.425518Z digest=sha256:8af91117a9268f532d7db121451644f5e06c1c75de2316f2f9785ae6ad6af471

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.523538Z digest=sha256:47332cee72d14ccb820b34ca22fe396e2aea30986e704dfecc9402f2dceaf658

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.673635Z digest=sha256:679f1d004033765339e33711ceb70c90a003be3382e2013cab292ab5d312ae07

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=sha256:7c51e221412a7b564bb67e1751762b33e80951f955f1421a54be1d350456c32d

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=sha256:49698048fb72d01b78b9594a7193915110c3dba5b22f150389533eecebcc1a3a

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=sha256:16aaa6950992d0851d28324a2531da19f003c6ee56d59609bfe1d948c8545f88

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=sha256:444281c6b1363c57f5d28fd9a61f6139d4b5f18366ef66981d9275db5433d6e4

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=sha256:8e13f478c972e3d94bed1e03286cc2b915c7121f4a35e6f577927bab188f6078

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.262350Z digest=sha256:22b9a9ffc4114a8f9341d823985e421204d7cfa1b3e4be2f31d116c6c31ceea4

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=sha256:25ed9f21af2399e4a318a2c69304065e922d9182053a08d03f2f02897ea02728

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.446109Z digest=sha256:f7abe0ff031c3db444e5fd8d8b05e6cacc1ae7dcd65373abacf6bf6a1402713b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.534554Z digest=sha256:02d3b826790292a117029ff5f6af331150329d323658f9034dbc664478683f14

Pith citing papers

No inbound Pith citation observations are available.