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Paper Citation Record · LEDGER

SkillEvolver: Skill Learning as a Meta-Skill

As of 2 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 2 inbound Pith citation observations for arXiv:2605.10500.

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

pith.paper-citation-record.v1
2605.10500 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T04:56:14.360454Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-02T06:30:47.504484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T02:07:39.738165Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact8
  • verified fuzzy2
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 92294cd8-be33-4301-8f37-26b102fabd9f · outbound

This paper cites Equipping agents for the real world with agent skills.https://www.anthropic.

SkillEvolver: Skill Learning as a Meta-Skill Equipping agents for the real world with agent skills.https://www.anthropic

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T13:01:35.314919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:789cd246e0823cbfb019bd892c6e24945b2f853da47eb91b390a9d726a6f9919

Observation 848f6b46-f213-4a2d-bde9-a09c15cf8f2b · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

SkillEvolver: Skill Learning as a Meta-Skill MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-12T05:46:30.941927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:5259688a7b6ed0d8379e8149b0469c4e544cbce3829a803882eae2ea8706f25d

Observation f63106d8-8d3a-4842-857e-09c52255e1b1 · outbound

This paper cites Automated Design of Agentic Systems.

SkillEvolver: Skill Learning as a Meta-Skill Automated Design of Agentic Systems

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-15T08:07:55.640311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:0a2275087caed61609c106807034721b57c9ba38d77f029e32b75ee49960b29b

Observation f6f73715-8dfb-4d17-abc8-ac1efc619813 · outbound

This paper cites Organizing, orchestrating, and benchmarking agent skills at ecosystem scale.

SkillEvolver: Skill Learning as a Meta-Skill Organizing, orchestrating, and benchmarking agent skills at ecosystem scale

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:46:31.029340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:c75d6a09d29be685e8f182d80959c25ffc83538d184dca84c115bf6685e2fa2b

Observation d6d32728-eb16-4a3c-8913-79d7da0459f8 · outbound

This paper cites Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills.

SkillEvolver: Skill Learning as a Meta-Skill Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-12T05:46:30.928072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:4f1ca59ee5ef5cf0aab88a02b46dd8b47e8c394a4c0f8a8622c2c31b9afe083a

Observation 87ebedb2-cfcf-45c5-9869-51336882fdf0 · outbound

This paper cites KernelBench: Can LLMs Write Efficient GPU Kernels?.

SkillEvolver: Skill Learning as a Meta-Skill KernelBench: Can LLMs Write Efficient GPU Kernels?

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:55:02.220088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:68fe763dafe15d249dc70581b4fa2cb14c0afe5b84a60ff4f0b3fb9dc5a3ab2e

Observation 03638dd5-7295-4066-9fb8-539bfbdc369b · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

SkillEvolver: Skill Learning as a Meta-Skill Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-05-12T05:46:30.906822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:62bc670fba0b101fe7df2357587d05862cea71073be2a1fb6fbe8bccfdb71b72

Observation 3c960811-bc23-4655-8161-f73b79095dc4 · outbound

This paper cites Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents.

SkillEvolver: Skill Learning as a Meta-Skill Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:46:30.933210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:efdb5cdb96ad1bce3ccdefd99352be3eea77c3f8002771637c79db028c6eed75

Observation 59010b3b-2a9b-479d-9364-df0dc9b88fa4 · outbound

This paper cites Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory.

SkillEvolver: Skill Learning as a Meta-Skill Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:46:31.048570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:0a24094e8a91edb58963a9678b9a994aeba545e1dcf3fa4e44cce5d02c307460

Observation 61e913e9-02c4-4252-a927-aa2ef860b3f3 · outbound

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

SkillEvolver: Skill Learning as a Meta-Skill Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 10

Resolution
metadata mismatch
local_arxiv, observed 2026-05-12T05:46:30.948378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:d0a3a7cff1a766f0f1d506a8c05b592870e39efe8048f406be6d6ddc3afeabcf

Observation 63f042e9-10f0-4dae-b957-99191be3249f · outbound

This paper cites Executable Code Actions Elicit Better LLM Agents.

SkillEvolver: Skill Learning as a Meta-Skill Executable Code Actions Elicit Better LLM Agents

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:46:30.957751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:af3343914bcf2988574b809600fab0ddf37dbb7a431301548ec21152cd320110

Observation 14eb192a-5cc7-47fb-b950-0363f446340b · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

SkillEvolver: Skill Learning as a Meta-Skill AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-05-12T05:46:30.987918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:f0506acc18facd843a7e138793c43a523d294a8fc80a16b8e76c00c0e3fca236

Observation 6dd35670-2a65-4d18-9aaf-70323d280613 · outbound

This paper cites SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning.

SkillEvolver: Skill Learning as a Meta-Skill SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T11:39:12.115659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:7f92f61c4b6566958d5a4936e501b9e8b353a42f4b69e791fec5c00536f1b69b

Observation 33f74d29-76f4-4e1b-b64f-3f9ab3bfbc31 · outbound

This paper cites TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks.

SkillEvolver: Skill Learning as a Meta-Skill TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T22:39:31.128039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:9bc0f2a8f1bf7fd09c2974d769d186bdaa4af1517869929083362525cd7b4463

Observation 61689bf8-4669-4398-b397-9e2abdfa92c1 · outbound

This paper cites Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward.

SkillEvolver: Skill Learning as a Meta-Skill Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:39:45.524165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:4a6a6ff93c50f01d59e80df102a76a6ff7179a652aa1a64926bcb23c794ad05d

Observation 239db0e1-a7d8-4f61-952c-2e23c251885e · outbound

This paper cites Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models.

SkillEvolver: Skill Learning as a Meta-Skill Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:44:08.223014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:8e302aacba930c907269722f859c83c7a3a32a644b5a3dbb98d82a646e8b287d

Observation 2cc14ec3-aadf-4009-85bd-cf654695c04b · outbound

This paper cites typically<2.5.

SkillEvolver: Skill Learning as a Meta-Skill typically<2.5

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T13:01:35.311101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-05-12T04:56:14.360454Z digest=sha256:f269247f88c38ab360d001c9e55ceafcd636480f2f9b3b37412ff66cb29ad8cf

Pith citing papers

Observation 6f740aa1-5572-49da-94f1-4177acdb0dbe · inbound

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis cites this paper.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SkillEvolver: Skill Learning as a Meta-Skill

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-31T14:26:53.326077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T14:26:53.326077Z digest=sha256:daa071f32fae1d483ededaf40ae4864e6da7bc32fd0bcb231485ae658e13135f

Observation 49fa7322-c24d-46ff-a38f-8ff3ab67991b · inbound

Agent Skills Matter: Inferring Proprietary Skills from Execution Trajectories cites this paper.

Agent Skills Matter: Inferring Proprietary Skills from Execution Trajectories SkillEvolver: Skill Learning as a Meta-Skill

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T02:07:39.738165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T02:07:39.738165Z digest=sha256:84886f9056b913f42afb6066f56f8c3da5b1f11ded526d39c34053643232f16e