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Paper Citation Record · LEDGER

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis

As of 10 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.24459.

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

pith.paper-citation-record.v1
2607.24459 v2

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T14:26:53.526424Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved29
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation efb5fef5-c9ee-41fb-9474-5fbdbfe7c056 · outbound

This paper cites DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation

Reference 1

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source=pdf_text observed=2026-07-31T14:26:52.135113Z digest=sha256:08c89a3f0b7441f3914289f0d0800878a15886115289055aa7a0fd9c265c3f5d

Observation 953d13e7-8382-465d-8004-40dcaafafc77 · outbound

This paper cites Towards an AI co-scientist.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Towards an AI co-scientist

Reference 3

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source=pdf_text observed=2026-07-31T14:26:52.243192Z digest=sha256:7c49c81790d74d98beafd1c0855871cf99ca1ea40e2f2f941a139466ca748a57

Observation e1ec44c5-a591-4626-a3ba-2d8beeebfd1a · outbound

This paper cites The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

Reference 4

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source=pdf_text observed=2026-07-31T14:26:52.302229Z digest=sha256:771360f06b553d023931e61a654a09cf0e2985d683b260851b4c492fd4251b6a

Observation dc4588f1-e253-4302-bc84-c90db88a60e3 · outbound

This paper cites ResearchCodeAgent: An LLM Multi-Agent System for Automated Codification of Research Methodologies.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis ResearchCodeAgent: An LLM Multi-Agent System for Automated Codification of Research Methodologies

Reference 5

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source=pdf_text observed=2026-07-31T14:26:52.355499Z digest=sha256:ba85897586392167c3fee84787fe9543ca1cc8759a9259bb4bc8f0d60c2f3708

Observation 88708047-8690-4df7-a06e-1ca8438e43fc · outbound

This paper cites ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research Code.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research Code

Reference 6

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source=pdf_text observed=2026-07-31T14:26:52.414276Z digest=sha256:26ab44cac22804c0fa11d0a40c85cb5d4269df082a21ff242dc1c34fad10caaa

Observation 1b400ff7-35eb-4983-852d-b97f00ebcb9a · outbound

This paper cites CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics

Reference 7

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source=pdf_text observed=2026-07-31T14:26:52.468976Z digest=sha256:6a1bab1ee0630622800e5e7a61c675cfc15883b4e63abc994d44508e16cd76e6

Observation 95dcb298-a3cb-428b-a234-2d35c075a376 · outbound

This paper cites FEM-Bench: A Structured Scientific Reasoning Benchmark for Evaluating Code-Generating LLMs.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis FEM-Bench: A Structured Scientific Reasoning Benchmark for Evaluating Code-Generating LLMs

Reference 8

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source=pdf_text observed=2026-07-31T14:26:52.524954Z digest=sha256:1e7fdb06811b05854ee02cad072fa41e3ea0b8f77d23414b0d807745ec5e5809

Observation b1671350-b6c5-468f-a93d-103fbf247634 · outbound

This paper cites SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks

Reference 9

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source=pdf_text observed=2026-07-31T14:26:52.580357Z digest=sha256:f9307d00f4143038fcb3a1f2ea8261d5e5a1386c40d279b0b9d103eed734a94d

Observation 7c01d3f1-0b67-4721-98cf-6de0fdfc3de0 · outbound

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

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SkillOpt: Executive Strategy for Self-Evolving Agent Skills

Reference 11

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source=pdf_text observed=2026-07-31T14:26:52.687659Z digest=sha256:6bf39ab34677aa4965f948f423066dcef86ba263f7b2c8b13a4a92c0a36a70ff

Observation 91d505aa-0bcd-4b78-b6cb-a6df568489e0 · outbound

This paper cites ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory

Reference 12

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source=pdf_text observed=2026-07-31T14:26:52.745085Z digest=sha256:1616339521a30bded375738e6dd61f7a119bdda00f26c1824b61f36291349779

Observation 1955fe08-dfff-491b-b70c-bd1edabf1e95 · outbound

This paper cites MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents

Reference 13

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source=pdf_text observed=2026-07-31T14:26:52.783851Z digest=sha256:84cfd98c92d1e7707becb1d05b0560d2bf5aa3bfe59ccc739ffaf8fff7842084

Observation 894dbc8c-7a03-4632-a50a-741d2b61d0c1 · outbound

This paper cites MemEvolve: Meta-Evolution of Agent Memory Systems.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis MemEvolve: Meta-Evolution of Agent Memory Systems

Reference 14

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source=pdf_text observed=2026-07-31T14:26:52.814861Z digest=sha256:665784ae1d4d151bae9dac7a19026da95bcf83a0d96fed62b11a2b39b0aead09

Observation bd754b38-33b6-44c1-8392-792f2504531b · outbound

This paper cites SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization

Reference 15

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source=pdf_text observed=2026-07-31T14:26:52.847676Z digest=sha256:9be63a3bb4872d3f66d28d22d51d2ce339f8db8876cecce799b035e1d1261faf

Observation a903c2d9-fb6d-418b-a451-f7f76918fc81 · outbound

This paper cites Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning

Reference 16

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source=pdf_text observed=2026-07-31T14:26:52.884915Z digest=sha256:5c0e9d5294b2e2d5e70102ddd5b530e104082776641ebece09d4e156c886de4d

Observation 2bd9eda8-ea2c-4103-b8ee-c393e2d6be20 · outbound

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

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

Reference 17

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source=pdf_text observed=2026-07-31T14:26:52.947868Z digest=sha256:a1201266537a21d4b12e20a8ed23273726a37b1d1796434b1ee2eb5d7eb04a8f

Observation e13dcb47-08fe-43d7-bb38-5877c2b86d92 · outbound

This paper cites Skill-to-lora: From using skills to learning behaviors for token- efficient llm agents.arXiv preprint arXiv:2606.16769,.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Skill-to-lora: From using skills to learning behaviors for token- efficient llm agents.arXiv preprint arXiv:2606.16769,

Reference 18

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source=pdf_text observed=2026-07-31T14:26:52.990312Z digest=sha256:5a9c63df90d1b54df22fa1bac05d6ecbd3b9f81915369027d7dc7eb3eef60420

Observation 41d2b364-9ca8-404d-9205-a685dd5fa552 · outbound

This paper cites SciCode: A Research Coding Benchmark Curated by Scientists.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SciCode: A Research Coding Benchmark Curated by Scientists

Reference 19

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source=pdf_text observed=2026-07-31T14:26:52.999650Z digest=sha256:2d2fd13abde6b79ba93444a8e96a98930c9bdb501d6e674eb5d89afd7bf4aeb1

Observation 705f215e-bd51-4807-98d3-2c977af3077c · outbound

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

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory

Reference 20

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source=pdf_text observed=2026-07-31T14:26:53.039628Z digest=sha256:161a9ef1e78db13174fae34bc34f81b40371000ce4bd09788dffeca44ad3ce19

Observation 213a8350-52d6-4f2e-8f6c-8f0cec528fd6 · outbound

This paper cites Memp: Exploring Agent Procedural Memory.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Memp: Exploring Agent Procedural Memory

Reference 21

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source=pdf_text observed=2026-07-31T14:26:53.080412Z digest=sha256:81f1107c53bf6f824601b0fd106e9278f05ea968c6cc4832055e1c3498088118

Observation 50f4d99e-fc9c-464a-a3f5-2f2fa16b574d · outbound

This paper cites MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory

Reference 22

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source=pdf_text observed=2026-07-31T14:26:53.121891Z digest=sha256:0df454b5c574317264557b2e26f9532b241b689ed5e2e2b0f5a532eb901249ba

Observation 7c758dc3-eeda-4584-8bb4-e727d4695ab8 · outbound

This paper cites Recursive Self-Evolving Agents via Held-Out Selection.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Recursive Self-Evolving Agents via Held-Out Selection

Reference 23

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source=pdf_text observed=2026-07-31T14:26:53.161111Z digest=sha256:1175fcbf706ac99efb98e4a7334887938b1175fb827442bd83150322fea34035

Observation 386d5f13-44ae-410d-b80b-25743bacbd80 · outbound

This paper cites Organizing, orchestrating, and benchmarking agent skills at ecosystem scale.arXiv preprint arXiv:2603.02176, 2026b.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Organizing, orchestrating, and benchmarking agent skills at ecosystem scale.arXiv preprint arXiv:2603.02176, 2026b

Reference 24

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source=pdf_text observed=2026-07-31T14:26:53.201344Z digest=sha256:075fb0740723f726c446c7e2a22e5677c5b6202a5c8b7dff3d115e02499ec07f

Observation 5a4212b1-8fd5-4d69-8bfc-09ed61d7cbd4 · outbound

This paper cites SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering

Reference 25

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source=pdf_text observed=2026-07-31T14:26:53.276008Z digest=sha256:230e88f3f79d9e25c53f885561888b85a6367a902930704453fe312949560279

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

This paper cites SkillEvolver: Skill Learning as a Meta-Skill.

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

Reference 26

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source=pdf_text observed=2026-07-31T14:26:53.326077Z digest=sha256:946fd23c533bc032eceff0571aa4e9d13616bce960cee88e08172c25c04b3b6c

Observation 27abc2cd-ff60-4c66-a258-57b2d4a257cc · outbound

This paper cites Skillwiki: A living knowledge infrastruc- ture for agent skills.arXiv preprint arXiv:2606.16523, 2026b.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Skillwiki: A living knowledge infrastruc- ture for agent skills.arXiv preprint arXiv:2606.16523, 2026b

Reference 27

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source=pdf_text observed=2026-07-31T14:26:53.398468Z digest=sha256:38904c0719d5d6cace81c0d5403908475396d9ed04b6c52b484e24d56eea7ff1

Observation 966d1149-01dd-491d-90c4-eda8ad39d53d · outbound

This paper cites AgentTrap: Measuring Runtime Trust Failures in Third-Party Agent Skills.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis AgentTrap: Measuring Runtime Trust Failures in Third-Party Agent Skills

Reference 28

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source=pdf_text observed=2026-07-31T14:26:53.427047Z digest=sha256:f3dc6ab53a47722c83cf4d170f0fb90a341d5f066aae5db32e8b20e81009feb2

Observation d71d55c9-d00c-46ed-af8d-77bae1e181bf · outbound

This paper cites Skills Are Not Islands: Measuring Dependency and Risk in Agent Skill Supply Chains.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Skills Are Not Islands: Measuring Dependency and Risk in Agent Skill Supply Chains

Reference 29

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source=pdf_text observed=2026-07-31T14:26:53.476943Z digest=sha256:2b7153affd6256eafa44406c361ef72a87096575615df0702cafdc444751a276

Observation 4c80ce6f-79b9-4e35-a9d9-77c7d4f71c57 · outbound

This paper cites OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation

Reference 30

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source=pdf_text observed=2026-07-31T14:26:53.526424Z digest=sha256:a0ec65562161d3773fcdde291c22b58b286febec62989d279a930ba15fa2ff4e

Observation bd08ec46-9c1c-4076-947d-82c7281644be · outbound

This paper cites TTRL: Test-Time Reinforcement Learning.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis TTRL: Test-Time Reinforcement Learning

Reference 2025

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source=pdf_text observed=2026-07-31T14:26:52.203859Z digest=sha256:8143814a1211dbb2f55b7b2b2efae239a85b14ffd7966b34f54db959c129a032

Observation b6a6a796-18b2-4416-b67f-87326af08f80 · outbound

This paper cites Inducing Programmatic Skills for Agentic Tasks.

From Execution to Capability: Scientific Experience Consolidation via Procedural Knowledge Synthesis Inducing Programmatic Skills for Agentic Tasks

Reference 2026

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source=pdf_text observed=2026-07-31T14:26:52.634156Z digest=sha256:770faabbc7e5c07f9e98c96946f9d74dd5896c80459505af95219113c3d2a9f2

Pith citing papers

No inbound Pith citation observations are available.