Paper Citation Record · LEDGER

Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2309.06687.

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

pith.paper-citation-record.v1
2309.06687 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:22:54.417804Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T16:56:07.747463Z

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 2f2bbcd7-286a-4a5a-89db-1f91cd5f7619 · inbound

Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning cites this paper.

Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T15:22:54.417804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b958d2e-df07-4cea-ac14-895a77e1f90f · inbound

An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems cites this paper.

An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 128

Resolution: unresolved; no resolver link, observed 2026-08-10T22:51:52.651459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd7e8063-7277-4126-8bfa-1885e31c7226 · inbound

MoColl: Agent-Based Specific and General Model Collaboration for Image Captioning cites this paper.

MoColl: Agent-Based Specific and General Model Collaboration for Image Captioning Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T22:23:27.785027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 655da6f3-23a5-4ae7-924e-f3069f1e2536 · inbound

MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models cites this paper.

MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T20:13:14.751918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bfd96f7-721e-46bc-821e-f6528fd842e8 · inbound

Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One cites this paper.

Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T15:24:59.961027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85bba71d-bfa2-4543-b947-d32463ec5e82 · inbound

Uncertainty-aware Reward Design Process cites this paper.

Uncertainty-aware Reward Design Process Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-06T20:39:14.628984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ed27b09-9f3c-49ab-9504-2c39f3a129f0 · inbound

Model-Based Proactive Cost Generation for Learning Safe Policies Offline with Limited Violation Data cites this paper.

Model-Based Proactive Cost Generation for Learning Safe Policies Offline with Limited Violation Data Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:56:07.753921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.