Paper Citation Record · LEDGER

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines?

As of 12 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2608.09629.

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

pith.paper-citation-record.v1
2608.09629 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:54:44.937402Z

measured 25 of 25 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

verified exact3
verified fuzzy9
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 90f49ae1-c508-41a2-b322-eb586790bbe5 · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.594470Z

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.

Observation 05e7eee7-1080-41e9-9764-5afd580e545a · outbound

This paper cites ExpeL: LLM Agents Are Experiential Learners.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? ExpeL: LLM Agents Are Experiential Learners

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.579169Z

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.

Observation e29e1ec4-8d86-4308-b194-77dc6cc697a8 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.837153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d4f495c-fdb1-4da9-bf09-f5bbe78a47ee · outbound

This paper cites Le, Denny Zhou, and Xinyun Chen.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Le, Denny Zhou, and Xinyun Chen

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.563677Z

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.

Observation 2c40d908-ec05-4c41-b250-4fe0f20395bd · outbound

This paper cites Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.847203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b557fa42-81e0-4951-8462-91e58caaa589 · outbound

This paper cites TextGrad: Automatic "Differentiation" via Text.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? TextGrad: Automatic "Differentiation" via Text

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.852127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5dcd19a-52ce-4d05-9136-4ce2a59364c1 · outbound

This paper cites Automated Design of Agentic Systems.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Automated Design of Agentic Systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.857300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5028ec18-10a3-4e53-9075-b30d206a8d11 · outbound

This paper cites AFlow: Automating Agentic Workflow Generation.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? AFlow: Automating Agentic Workflow Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.861803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95baf02a-e218-486f-9a6d-282f4c0e884c · outbound

This paper cites Agrawal, Shangyin Tan, Dilara Soylu, Noah Ziems, Rishi Khare, Krista Opsahl- Ong, Arnav Singhvi, Herumb Shandilya, Michael J.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Agrawal, Shangyin Tan, Dilara Soylu, Noah Ziems, Rishi Khare, Krista Opsahl- Ong, Arnav Singhvi, Herumb Shandilya, Michael J

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.547272Z

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.

Observation afd3fcf4-b2cd-4c8a-bdf9-6899d7b55ef3 · outbound

This paper cites Truly Self-Improving Agents Require Intrinsic Metacognitive Learning.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Truly Self-Improving Agents Require Intrinsic Metacognitive Learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.529953Z

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.

Observation d4635df7-c791-4b39-adb6-7a0517f81971 · outbound

This paper cites Harnessing Agentic Evolution.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Harnessing Agentic Evolution

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.875004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8c20357-89e1-475f-bb63-affeafd94255 · outbound

This paper cites Bayesian-Agent: Posterior-Guided Skill Evolution Across LLM Agent Harnesses.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Bayesian-Agent: Posterior-Guided Skill Evolution Across LLM Agent Harnesses

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-11T13:54:54.366704Z

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.

Observation 5f0532e4-f83a-4294-9ca8-f778589270f0 · outbound

This paper cites SkillOS: Learning Skill Curation for Self-Evolving Agents.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SkillOS: Learning Skill Curation for Self-Evolving Agents

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.884421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cd04951-4fa8-4e20-9eaf-9d19e1e91de0 · outbound

This paper cites Hypothesis-Driven Skill Optimization for LLM Agents.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Hypothesis-Driven Skill Optimization for LLM Agents

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T13:54:54.330106Z

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.

Observation b8c42358-6f07-48ff-960f-216d881f21f3 · outbound

This paper cites SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing

Reference 15

Resolution: verified exact; raw_fallback, observed 2026-08-11T13:54:54.308936Z

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.

Observation 0644e751-9f37-429e-add9-8ddc3650b748 · outbound

This paper cites SkillOpt: Executive Strategy for Self-Evolving Agent Skills.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SkillOpt: Executive Strategy for Self-Evolving Agent Skills

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.897656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da4d23c5-deee-4f2a-b833-3a410acc0df0 · outbound

This paper cites SkillOpt: Training Skills Like Weights.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SkillOpt: Training Skills Like Weights

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.514754Z

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.

Observation fe37ab15-13ea-4540-af23-bedc2de8b559 · outbound

This paper cites SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.906585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af04c6d8-e145-45fb-98c8-f43341dbb857 · outbound

This paper cites GPT-5.5 System Card.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? GPT-5.5 System Card

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.498915Z

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.

Observation 2117bed9-869d-4197-a5a1-265c06744f5d · outbound

This paper cites Qwen3.5: Towards Native Multimodal Agents.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? Qwen3.5: Towards Native Multimodal Agents

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.484306Z

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.

Observation 0598fad5-63da-47ee-ad28-28b844f920c0 · outbound

This paper cites SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.920228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfa6d926-2beb-4b81-b7d7-e17e30da0356 · outbound

This paper cites SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.924632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 519fd6b5-b61c-4a26-b932-adc6f540b9a2 · outbound

This paper cites OfficeQA Pro: An Enterprise Benchmark for End-to-End Grounded Reasoning.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? OfficeQA Pro: An Enterprise Benchmark for End-to-End Grounded Reasoning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.929052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7b09166-dffa-4c44-8ac3-cad99e8768a7 · outbound

This paper cites OfficeQA: Repository and benchmark documentation.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? OfficeQA: Repository and benchmark documentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:54:54.469583Z

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.

Observation 262a0275-14a5-4dc6-8a9a-5df6067ac037 · outbound

This paper cites LiveMathematicianBench: A Live Benchmark for Mathematician-Level Reasoning with Proof Sketches.

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines? LiveMathematicianBench: A Live Benchmark for Mathematician-Level Reasoning with Proof Sketches

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T13:54:44.937402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.