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Paper Citation Record · LEDGER

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.20587.

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

pith.paper-citation-record.v1
2310.20587 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:13:43.083091Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T14:25:59.320937Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 81473b10-146c-46ff-a5e4-ee96d5754ea7 · inbound

Agent AI: Surveying the Horizons of Multimodal Interaction cites this paper.

Agent AI: Surveying the Horizons of Multimodal Interaction Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 113

Resolution
verified exact
arxiv_id, observed 2026-05-18T14:25:59.323805Z

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=2026-05-18T14:25:58.876978Z digest=sha256:467ea26b0e6ccbb55cabacd4305508488e43ca2fe0b30fc3de1590d616ac54c1

Observation 77890aac-aa10-46ce-8d6d-e4fa63174938 · inbound

TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation cites this paper.

TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T16:12:26.052514Z

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=pdf_text observed=2026-05-17T16:12:25.980853Z digest=sha256:fbabddf0913b068297c42aaede3be76ca178d1f8e86cae10ae93c5ac2f64341b

Observation 6f3765b7-752a-414c-acc6-0bb795585cde · inbound

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving cites this paper.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T15:13:43.083091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:13:43.083091Z digest=sha256:79594187828c2183d456e799538525da3c6b4c26a450b7e432973cfea76ea305

Observation fa6ae2c6-7739-44b5-a371-55c774d36064 · inbound

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning cites this paper.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T12:55:52.772925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:55:52.772925Z digest=sha256:264aec4dc84975a55b9a0bcdc801a9c7da0db9fe22a9db269e595ab660400492

Observation 44e4d566-7d77-4f85-89ad-bee0d6a96c18 · inbound

Large Model Empowered Embodied AI: A Survey on Decision-Making and Embodied Learning cites this paper.

Large Model Empowered Embodied AI: A Survey on Decision-Making and Embodied Learning Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 169

Resolution
unresolved
no resolver link, observed 2026-08-05T20:31:51.654781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:31:51.654781Z digest=sha256:3b8e228232918350310f89de3c6af72e0a4d7de0d98c04fb3b03d95342f1b0ca