Paper Citation Record · LEDGER

Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2406.16218.

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

pith.paper-citation-record.v1
2406.16218 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:26:44.971047Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:39:30.783853Z

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 215f34e5-cb78-4abd-bae6-8d664bfbc452 · inbound

Natural Language Reinforcement Learning cites this paper.

Natural Language Reinforcement Learning Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.971047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 951835f2-a5bc-4ac0-befd-85cb9051d30a · inbound

Multi-Agent System for Cosmological Parameter Analysis cites this paper.

Multi-Agent System for Cosmological Parameter Analysis Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T05:26:14.104184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdb87e88-420e-4934-ac49-0bbb4b3d1c09 · inbound

Aviary: training language agents on challenging scientific tasks cites this paper.

Aviary: training language agents on challenging scientific tasks Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.523504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f7a0bab-b325-4aed-bf10-a1e17af7dd32 · inbound

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces cites this paper.

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:21:23.193228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ba241145-2577-46f8-aa81-c3e50cd1029c · inbound

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces cites this paper.

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.774418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9bb546e7-1886-4910-b1df-ded240f37b84 · inbound

Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.

Learning, Fast and Slow: Towards LLMs That Adapt Continually Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:07:18.400455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f74077c8-4448-4435-ad85-d5964237d666 · inbound

Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.

Learning, Fast and Slow: Towards LLMs That Adapt Continually Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:19:45.511166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 75ccd0cc-4644-4ef2-bcd3-8055773098ea · inbound

MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization cites this paper.

MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-20T06:13:05.293872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b55b14e5-aa67-4d81-8a0a-210bc2c47031 · inbound

Diagnosis Is Not Prescription: Linguistic Co-Adaptation Explains Patching Hazards in LLM Pipelines cites this paper.

Diagnosis Is Not Prescription: Linguistic Co-Adaptation Explains Patching Hazards in LLM Pipelines Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:54:42.008874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 657eb882-d2a1-4de6-b922-b61e4475fab6 · inbound

SPEAR: Code-Augmented Agentic Prompt Optimization cites this paper.

SPEAR: Code-Augmented Agentic Prompt Optimization Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-29T21:43:59.769526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 711cd5cc-80fc-4640-938c-7b6c89530213 · inbound

Marginal Advantage Accumulation for Memory-Driven Agent Self-Evolution cites this paper.

Marginal Advantage Accumulation for Memory-Driven Agent Self-Evolution Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:39:30.785893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7e24c6bc-e978-4394-a654-b4a3c2cfc91a · inbound

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization cites this paper.

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T06:02:25.649833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afa4c939-57e6-4c6b-a006-90c5380604c4 · inbound

A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization cites this paper.

A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-12T00:28:29.164750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.