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Paper Citation Record · LEDGER

Adapting LLM Agents with Universal Feedback in Communication

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.01444.

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

pith.paper-citation-record.v1
2310.01444 v3

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 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:49:22.466971Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T00:40:51.289393Z

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 67912c35-e889-4121-a4da-9fae28b5ad30 · inbound

From Laws to Motivation: Guiding Exploration through Law-Based Reasoning and Rewards cites this paper.

From Laws to Motivation: Guiding Exploration through Law-Based Reasoning and Rewards Adapting LLM Agents with Universal Feedback in Communication

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T13:49:22.466971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:49:22.466971Z digest=sha256:43b535694a9c2d48a91fca6d888c9fb0d22d15f9cba97d3349d53b66e9c27137

Observation 1502bab8-e189-4f4c-abef-4b9a0c3ff5b5 · inbound

Distributed Mixture-of-Agents for Edge Inference with Large Language Models cites this paper.

Distributed Mixture-of-Agents for Edge Inference with Large Language Models Adapting LLM Agents with Universal Feedback in Communication

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T23:05:46.398106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:05:46.398106Z digest=sha256:bf67d1dcc97876c3366ab0aba1c23ea09ab6bc8e4c8ca995000b4bcce0c27931

Observation d08040d7-3a41-4072-89ea-843205a52b92 · inbound

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis cites this paper.

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis Adapting LLM Agents with Universal Feedback in Communication

Reference 119

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:40:51.291979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-22T00:37:11.945418Z digest=sha256:a8bee19656d042d6adef501ded200d2bcde7bbb4c4b51eb10b70330aea5583ee

Observation 8bed3f79-8375-44ea-8451-49585e3de91a · inbound

VulRTex: A Reasoning-Guided Approach to Identify Vulnerabilities from Rich-Text Issue Report cites this paper.

VulRTex: A Reasoning-Guided Approach to Identify Vulnerabilities from Rich-Text Issue Report Adapting LLM Agents with Universal Feedback in Communication

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-05T10:40:24.792898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:40:24.792898Z digest=sha256:416c1f39b7079c8932cbb97b85afb8cfccc2d6ea492a32a18a8f51d323f35326

Observation 65921f39-1485-48ff-9cd8-271490c9f0b7 · inbound

Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains cites this paper.

Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains Adapting LLM Agents with Universal Feedback in Communication

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-20T05:48:04.485349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T05:45:02.563352Z digest=sha256:a2d1f3941cabfd9eb9dcb720bd1320fbe06a6dea1823a4c40262540f6e082854