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Paper Citation Record · LEDGER

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

As of 13 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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:30.916113Z digest=sha256:6ae3dfa4ca81549808bd60f20e665bf8e9e7dd68b9d667006c8212581f96294b

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:30.980647Z digest=sha256:f462d5ef959ed22a8ddf13f33bc505b9737d230f35b428212ddffc670350d284

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.080200Z digest=sha256:b55eddba711ebc565e8b60d56df73779aad23163a480746e32f948052a32a4cc

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.190307Z digest=sha256:647ef1c76575169a4326e7f21e206f9c02b71d356ddc80a51d8fcbe5f4f1694c

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.328397Z digest=sha256:2bf842f75fd23e6be8306328e2fd35d9595e00c1dfbf539008bc42358e0227a8

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.425518Z digest=sha256:282c380aac552072206f724bb7a229cb6b9acfb96cf992082a9e8b8d44233928

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.523538Z digest=sha256:4fc481a1da16189e80d05f0a8b5372972caea4a5fc2734d80a2bf5ef36c06614

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:31.673635Z digest=sha256:6df40f8ca2bc753eb89c1b813d6fb5c3587f398261bf191d86f1631b97d9f678

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:beecd64ae7c98730338f95282fa6eacbe17554de6b9a922046968c530bc0fd53

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=sha256:46f936147d14c6fc61265bbf0e3fdd37f45ba94d22f06f43acdf850c3457683b

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:e2c3554bd14a63df1eaeb467045da9fcfb3bc45e48fecfe0b7cbd82755166825

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=sha256:86f41b3cb91a1a78df339ceb651e77e387951de5215d9e80fb645367629f0f10

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=sha256:7f17ae9f495e1ae80abdf4cff5c6d91fcdd9886c1c39a37225748ed8d3064274

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.262350Z digest=sha256:26a5efa3241a038cf4e029f8da1892bc2771d60b38079f3595d782793ead2e88

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=sha256:9c69c26559de7ccec853c76f5c49e69c5e392effce731e929ccd7119a40ce202

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.446109Z digest=sha256:966ed978ce35ae2aa49bb1a70ff86623e8a720b58a0242f7f511cef167332567

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-05T16:13:32.534554Z digest=sha256:2dfb69a398d29026637861bfda3daad03ee7600985ca1c586bef7308d47d55d9

Pith citing papers

No inbound Pith citation observations are available.