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Paper Citation Record · LEDGER

How Can LLM Guide RL? A Value-Based Approach

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.16181.

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

pith.paper-citation-record.v1
2402.16181 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:39:02.321135Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-04T20:49:38.670045Z

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 3d02adea-a961-41c2-bc21-927f16262f28 · inbound

EvoVLMA: Evolutionary Vision-Language Model Adaptation cites this paper.

EvoVLMA: Evolutionary Vision-Language Model Adaptation How Can LLM Guide RL? A Value-Based Approach

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-06T05:39:02.321135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:39:02.321135Z digest=sha256:b4ad899d9f147a757f42ee19c0ed687321129a17abe4f77fef627a603440edb8

Observation a83b7b2c-630d-41c5-8d9e-db6c08b215e3 · inbound

Accelerating Reinforcement Learning Algorithms Convergence using Pre-trained Large Language Models as Tutors With Advice Reusing cites this paper.

Accelerating Reinforcement Learning Algorithms Convergence using Pre-trained Large Language Models as Tutors With Advice Reusing How Can LLM Guide RL? A Value-Based Approach

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-04T20:49:38.673521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-04T20:49:37.369250Z digest=sha256:484e94240cb0855da292ea66b959dd7af34e36730bd67eea931aa06a1ccd83cc

Observation 8d8e9f2e-b3b5-446e-9ad1-4a64d29f34d9 · inbound

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models cites this paper.

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models How Can LLM Guide RL? A Value-Based Approach

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-02T20:14:04.194029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:14:04.194029Z digest=sha256:f131f32c5de0d8dd53cf76e4c714543ad8171b4f4f61645c5d46e2fd0952597e