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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=sha256:87052d1f8efb94ccfcd74b572bac005d606b4604e2d476ff90acc1ac2501edb3

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=sha256:6833112270a3b53c5bd8a585aba825f6e8ab2b600fa02663043804a92f7d7c39

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:f248d05bf17080546d7d4226b21d25f595f3d2e26d39f176d1f51aeb9a1bcac2

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:e02e7c57019081857de15bc849c933319f6178d3e271f3a334e75a3f6fa7472c

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=sha256:60e09633aeb75e169cb879317db2d9e67df2f7c507e4ec961a49494f60d90fc5

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=sha256:093ccf5f9aa8eddb448cdeb27854a53dce7ac1dc252530eecd7047eed656619c

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=sha256:8069701d0ddbec9518a2fd0225db1297804379b20f62c9379452b5c0a16aace5

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=sha256:872460e937790312934b5f04d04b19e92a362cf195122771020dfa9f4e8ea8e2

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=sha256:9ab774d825eeab360f1aa3b8290f4dc04355f9662a93b630cc70b3b8c376bc48

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=sha256:0485b9b8dad7e92daceb3b4a52e782f62970866874683a78a97cd9aa1e70960c

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=sha256:259b3e3b2aedd834118c344a67afdf6af38078c40619a9f151147239bcab3f5b

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=sha256:35699ac4472e55d0555f710ec606071e646838c04f8ae156a2f0cb7fd7846554

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:b77e8b753fec03c1fd32ae12669f24e256f8b650d3f7ff4d1fde73e370558e29

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=sha256:3cfdd981a2b07e2738e37d0bdb8818dbc67215dc327056e30d9d84142b1e0daf

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=sha256:587acba4841163e0b23deb826480e9e79f12abe51a0af1c4da2002a0d959018c

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=sha256:20505abb7d723ad7b01aef448f9c5821983392683ad8099d2266eec5fef79431

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:c9084778220d36777582704bc3dffb86ef7fcc1a56fa95f2718487c468032fcf

Pith citing papers

No inbound Pith citation observations are available.