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Paper Citation Record · LEDGER

REvolve: Reward Evolution with Large Language Models using Human Feedback

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.01309.

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

pith.paper-citation-record.v1
2406.01309 v4

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 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:25:15.375581Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T03:50:57.904902Z

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 2f0f915a-6f5c-4c02-8e53-eae751bf7482 · inbound

VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving cites this paper.

VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving REvolve: Reward Evolution with Large Language Models using Human Feedback

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T11:25:15.375581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:25:15.375581Z digest=sha256:d9b8920870b0df8d89c0397690032cf744efdca734e0eddd3c784c28d31d6ebd

Observation 68c4d726-39aa-4b74-bb02-d46ad8466384 · inbound

LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models cites this paper.

LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models REvolve: Reward Evolution with Large Language Models using Human Feedback

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T21:23:20.512620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:23:20.512620Z digest=sha256:e34672396fdd7e26480f24ebf896fcc386ae0529f944e5e0a08ba64aac95021e

Observation 32bbd080-5f8a-4eb2-9594-d8ed12c7c23e · inbound

Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings cites this paper.

Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings REvolve: Reward Evolution with Large Language Models using Human Feedback

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T12:15:37.686427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:15:37.686427Z digest=sha256:805633a9c1d9857bb456be8064560bdafd59989fb7f74c34a3b3ef99b73910ba

Observation 100eb8c9-fa60-476b-ba4a-94b9a55be990 · inbound

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning cites this paper.

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning REvolve: Reward Evolution with Large Language Models using Human Feedback

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:00:35.168345Z

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=pdf_text observed=2026-05-08T19:14:22.162163Z digest=sha256:3043f80abc7573ec68be7f6288b19eb7292aac6a3aaf74cae8a5f5b8cef86780

Observation 89435e50-2fd0-4c7d-b35e-8d808c65bd3a · inbound

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning cites this paper.

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning REvolve: Reward Evolution with Large Language Models using Human Feedback

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:50:57.911903Z

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=pdf_text observed=2026-05-11T02:10:46.725354Z digest=sha256:b012327dbc995e383f003352c2ace4ec148e73339c25989d31633724ca75d544