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Paper Citation Record · LEDGER

The Scaling Laws of Skills in LLM Agent Systems

As of 15 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 2 inbound Pith citation observations for arXiv:2605.16508.

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

pith.paper-citation-record.v1
2605.16508 v1

Coverage vector

measured 90 of 90 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T18:10:08.737710Z

measured 92 of 92 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:04:12.409948Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

90 of 90 outbound references displayed

  • verified exact36
  • verified fuzzy38
  • unresolved12
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 086ee6ce-ff99-4d97-bc83-0abd09e1803f · outbound

This paper cites A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6):186345.

The Scaling Laws of Skills in LLM Agent Systems A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6):186345

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.190139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:41766c9f1e49533ad49a821d4cea021e6c9873745292e74bce85d6954eafc670

Observation abe466a0-6ff7-44b0-b3ee-0f4272ea2695 · outbound

This paper cites Llm-based agents for tool learning: A survey.Data Science and Engineering.

The Scaling Laws of Skills in LLM Agent Systems Llm-based agents for tool learning: A survey.Data Science and Engineering

Reference 2

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verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.245004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:037b4ea3ed3d7eeb942674d13c76ed39d86c7c548edb8273b0ffadf3c41ae315

Observation 78afe9d4-8717-428e-a66b-15fe61a9b6d8 · outbound

This paper cites Survey on Evaluation of LLM-based Agents.

The Scaling Laws of Skills in LLM Agent Systems Survey on Evaluation of LLM-based Agents

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.663969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:c10d54f1a03349d5309da2e56bb831211574ca1b8ee3ae5dc49762c106e7867b

Observation 86f48876-50e5-4cff-b170-0b0dc1747511 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

The Scaling Laws of Skills in LLM Agent Systems Toolformer: Language models can teach themselves to use tools

Reference 4

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verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.307101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:092accc9dafbacf81b030eba561c157b490a44968dbd26294471a82899682568

Observation 5ef10311-38bd-459e-95ed-fb1d1ab8968c · outbound

This paper cites ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.

The Scaling Laws of Skills in LLM Agent Systems ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.656732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f1726a388a7e75ae56cfa79e3794581b98df2aee14eea2a4c229b89726695423

Observation 14b7ce0d-9ae0-4890-b3a1-de9b526baf26 · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

The Scaling Laws of Skills in LLM Agent Systems Gorilla: Large Language Model Connected with Massive APIs

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.565097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:39693e25c420e73a48fea550e2c2eca45d6738312cb99c263a6a384961cf23e4

Observation 6c47fd8d-faee-444e-8d3f-da9f3b66d61f · outbound

This paper cites API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs.

The Scaling Laws of Skills in LLM Agent Systems API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.648430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:76106dbf4e56a0a938cef945110cd242354ae2cfcf4f98be92853fb5a4a0877e

Observation ba5974ba-b04f-4dc3-92ec-390f9993e4d4 · outbound

This paper cites TaskBench: Benchmarking Large Language Models for Task Automation.

The Scaling Laws of Skills in LLM Agent Systems TaskBench: Benchmarking Large Language Models for Task Automation

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T18:13:37.585700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:dfb3eadf4f4761251807c49535d6fe9a24800f04d12a63ce6b472da96a0d8b74

Observation 29efb6f4-009e-44cc-aa79-de12ee4cadf8 · outbound

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

The Scaling Laws of Skills in LLM Agent Systems SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.611028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:a6f54f9efd59e63dc00671bd1f900ffd2c4c76e56c7ec3477eebea4ee95868fd

Observation 184c67a8-1d2d-4784-b614-418db3778f0e · outbound

This paper cites SkillRouter: Skill Routing for LLM Agents at Scale.

The Scaling Laws of Skills in LLM Agent Systems SkillRouter: Skill Routing for LLM Agents at Scale

Reference 10

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verified exact
arxiv_id, observed 2026-07-21T02:21:33.547916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:862a9febede5a8e00cba39ceb926e41319281ad00f264d87280e586edf6172bd

Observation 0f296bff-16ee-4244-b22e-70a0502e151f · outbound

This paper cites Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models.

The Scaling Laws of Skills in LLM Agent Systems Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

Reference 11

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local_arxiv, observed 2026-05-20T18:13:37.582017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:00382dceb3ac2d854969c6503db0aa781027bb6fa01526986a2ee6c8019973ad

Observation 3f4468cb-6236-49e1-8623-da83a4b65232 · outbound

This paper cites AI4Research: A Survey of Artificial Intelligence for Scientific Research.

The Scaling Laws of Skills in LLM Agent Systems AI4Research: A Survey of Artificial Intelligence for Scientific Research

Reference 12

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arxiv_id, observed 2026-05-20T18:13:37.629993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:4c3f0979b6714dd452171115f582ccbf7520343d6eeba0e6176243360b8bef88

Observation d717f805-c881-4bdf-812b-29608f94e23c · outbound

This paper cites A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence.

The Scaling Laws of Skills in LLM Agent Systems A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.660326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:4aa5052b1e7dd4d3b776d8a4d7962135dcebf23bb4b85d75b75d5294222cd6cf

Observation 99626512-9bdd-434a-8b4f-86492da096ab · outbound

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

The Scaling Laws of Skills in LLM Agent Systems Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward

Reference 14

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verified exact
local_arxiv, observed 2026-05-20T18:13:37.623312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:ed3fa7d5f85ebecb4a2a76c162aea53b2b0f610c5af749691cef28505789ccee

Observation 02ddc2c7-5774-4d2c-9204-2efd240ec33b · outbound

This paper cites ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases.

The Scaling Laws of Skills in LLM Agent Systems ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases

Reference 15

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local_arxiv, observed 2026-05-20T18:13:37.614372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:35efacf3bae3a83b3d3fee0ca69459d4e158c470cb2d19ade32538d9298bd115

Observation 198895a7-6067-4064-bb95-c8445a178843 · outbound

This paper cites OpenAgents: An Open Platform for Language Agents in the Wild.

The Scaling Laws of Skills in LLM Agent Systems OpenAgents: An Open Platform for Language Agents in the Wild

Reference 16

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verified exact
arxiv_id, observed 2026-05-20T18:13:37.589261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:3dee187681b107dd6b22e758730a6dd509cd56b89fded497020aef4fc5fea517

Observation 895cdbad-1a46-4161-8799-dafbe8381c36 · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

The Scaling Laws of Skills in LLM Agent Systems AgentBench: Evaluating LLMs as Agents

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.653968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:042b374bd887e909e89789c70e62ead5e08636a0818bea5c2414f486d6d24506

Observation 684a6776-819c-41d8-b0e1-8815fd6f8932 · outbound

This paper cites SoK: Agentic Skills -- Beyond Tool Use in LLM Agents.

The Scaling Laws of Skills in LLM Agent Systems SoK: Agentic Skills -- Beyond Tool Use in LLM Agents

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.617718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:a0ccedb346d7e38f111b1b2fc9ca8c3f7750a71c1d0aa9f3b49637aa77096889

Observation 2fc5809e-1e62-4e1d-98c9-c1437ec70499 · outbound

This paper cites ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario.

The Scaling Laws of Skills in LLM Agent Systems ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Reference 19

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arxiv_id, observed 2026-05-20T18:13:37.604607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:0c84d1650559078457704e719da4eaabe3868b546ed8367e59d27458b7cb66f0

Observation d840394f-0ef3-4aeb-9d12-5f45863a08c9 · outbound

This paper cites BiasBusters: Uncovering and mitigating tool selection bias in large language models.

The Scaling Laws of Skills in LLM Agent Systems BiasBusters: Uncovering and mitigating tool selection bias in large language models

Reference 20

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raw_fallback, observed 2026-05-20T18:13:38.232635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f2170b6635ec247ee2093858727b638ce18340e4a192138748b71b33b9a1a3e8

Observation 4bb0b22e-062d-4b84-8d74-03a8fb5a8bdb · outbound

This paper cites xRouter: Training cost-aware LLMs orchestration system via reinforcement learning.

The Scaling Laws of Skills in LLM Agent Systems xRouter: Training cost-aware LLMs orchestration system via reinforcement learning

Reference 21

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arxiv_id, observed 2026-05-20T18:13:37.592545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:a4915c094a8e7d4cc1d8836baf0895d9745d9193acfabbef51176061bc8ed203

Observation 2f5bf26c-c4ae-45e2-958c-9f440d63d918 · outbound

This paper cites EvoRoute: Experience-driven self-routing LLM agent systems.

The Scaling Laws of Skills in LLM Agent Systems EvoRoute: Experience-driven self-routing LLM agent systems

Reference 22

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arxiv_id, observed 2026-05-20T18:13:37.595724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:20487de19e7a5d4b370c8a1f554daca876d817402a7760bbc5b2267658d65448

Observation 1ecc9216-24d2-4289-813c-e07338043a54 · outbound

This paper cites Autotool: Efficient tool selection for large language model agents.

The Scaling Laws of Skills in LLM Agent Systems Autotool: Efficient tool selection for large language model agents

Reference 23

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verified exact
arxiv_id, observed 2026-05-20T18:13:37.558550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:3d159b83f738b78ab58acbb8ada96cfa688c4c354d7b9135df16a2fe7361acf5

Observation b858b10f-5f6b-4602-914c-796b297b939f · outbound

This paper cites Meta- toolagent: Towards generalizable tool usage in llms through meta-learning.

The Scaling Laws of Skills in LLM Agent Systems Meta- toolagent: Towards generalizable tool usage in llms through meta-learning

Reference 24

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verified exact
arxiv_id, observed 2026-05-20T18:13:37.601673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:654f0f2bcf4d8aa41d9942bb6e05bc355d095ad1ed826a744c0fd8562c640ab1

Observation d20aaca6-7409-4b70-b84d-d4f5f3789a3a · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

The Scaling Laws of Skills in LLM Agent Systems ReAct: Synergizing reasoning and acting in language models

Reference 25

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verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.247147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:dae370bedf42bfb221c85ba8b1eb03b9d6c6f6e083645b7cb605f59df2d16b62

Observation 789429eb-5914-4e19-bb43-51cce8facaf1 · outbound

This paper cites Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models.

The Scaling Laws of Skills in LLM Agent Systems Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models

Reference 26

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verified exact
doi, observed 2026-05-20T18:13:37.089564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:159855a0a46b0f772944e3e2d1db2efe9fceaa68015192104c7caa8815a3b8c6

Observation 07649ac1-5d7c-4286-8996-b488f1925fc8 · outbound

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

The Scaling Laws of Skills in LLM Agent Systems Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 27

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verified exact
local_arxiv, observed 2026-05-20T18:13:37.651300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:26023f2160a9bd3e9a55d3859a9d73f7e727dfb2855ea051185a5b1a84a72602

Observation 457a730f-24ca-452d-b02a-896fbceab62c · outbound

This paper cites HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face.

The Scaling Laws of Skills in LLM Agent Systems HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face

Reference 28

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verified exact
local_arxiv, observed 2026-05-20T18:13:37.633626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:6071dd9b0deb8f84f2d4413e6b756556d2786bb26022ea7443e978fcebf34560

Observation f1f33f56-91ca-480d-b172-09c6962f4dd1 · outbound

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

The Scaling Laws of Skills in LLM Agent Systems MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 29

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verified exact
local_arxiv, observed 2026-05-20T18:13:37.572049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:0579547353b1d7e4f1956bd21cffb90fe60a400e9e361c09216ed15617a555a1

Observation 7cdb49c2-661a-4d66-b7cd-4b241dfe02f5 · outbound

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

The Scaling Laws of Skills in LLM Agent Systems Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 30

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local_arxiv, observed 2026-05-20T18:13:37.645812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f55b7e13e5fa2a89e7c157c001a6f608144d0e9384f4c6183a98dc24adf49ed0

Observation 42700f14-ab5b-497a-95be-078776e5d02b · outbound

This paper cites TaskWeaver: A Code-First Agent Framework.

The Scaling Laws of Skills in LLM Agent Systems TaskWeaver: A Code-First Agent Framework

Reference 31

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arxiv_id, observed 2026-05-20T18:13:37.561727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:b1e2413e44a86b541b8e96d0411a19aef68835ba8a375520ac45426ad231d708

Observation 310ebe67-b272-46ba-a4de-a4da00752f82 · outbound

This paper cites MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback.

The Scaling Laws of Skills in LLM Agent Systems MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback

Reference 32

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arxiv_id, observed 2026-05-20T18:13:37.568810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:c5acb1c3933043f8ba6f48009b8130b0e2e7df7a78803b7096d58cd11b6fdb71

Observation f2c3f68d-2ea1-487c-9076-26900b9fb1f8 · outbound

This paper cites AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls.

The Scaling Laws of Skills in LLM Agent Systems AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls

Reference 33

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arxiv_id, observed 2026-05-20T18:13:37.636657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:02f6abe6e45df80fc8b0dc35ecac45a305dd990f18bfb3f52595bf64fd2a2a11

Observation 83459fa1-372a-4927-952a-000830629ab0 · outbound

This paper cites Evaluation and Benchmarking of LLM Agents: A Survey.

The Scaling Laws of Skills in LLM Agent Systems Evaluation and Benchmarking of LLM Agents: A Survey

Reference 34

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arxiv_id, observed 2026-05-20T18:13:37.607891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:30cd651db6ee3832db6a5da5d7f0e05b353fa14ce357db9fa79e25e9244fae33

Observation fc932d3b-c710-4349-88c7-e513da7f760b · outbound

This paper cites Scaling Laws for Neural Language Models.

The Scaling Laws of Skills in LLM Agent Systems Scaling Laws for Neural Language Models

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.620143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:4c795d2d83153541166d0fab313230a579a5a0c875a40b265c82058cb8eaa407

Observation 15ce077f-a45d-4547-987a-f19ff33177ad · outbound

This paper cites Training Compute-Optimal Large Language Models.

The Scaling Laws of Skills in LLM Agent Systems Training Compute-Optimal Large Language Models

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.554400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:772b98d8c2f1f00066ff6bd94de80d7a2d865b91e4d9c43041ac79961c903782

Observation 74f716e2-c62b-4f3a-9b15-75c628b4a8bf · outbound

This paper cites Emergent abilities of large language models.Transactions on Machine Learning Research.

The Scaling Laws of Skills in LLM Agent Systems Emergent abilities of large language models.Transactions on Machine Learning Research

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.242491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:882b438cbac96b3a9ca97f5cbfbe6412b6d851e935b2309eb9b73be5d4254205

Observation de746de4-bb58-4061-94f4-06fdc71e5905 · outbound

This paper cites Chatterji, Sharan Narang, Mike Lewis, and Dieuwke Hupkes.

The Scaling Laws of Skills in LLM Agent Systems Chatterji, Sharan Narang, Mike Lewis, and Dieuwke Hupkes

Reference 38

Resolution
verified exact
doi, observed 2026-05-20T18:13:37.083004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:d7f2d9f63da2ec7a1cdbe77dfbc16356467906c10f3583b8f0ae22a95c050ff6

Observation d369ce13-6fc6-4972-a411-e516dcbd093f · outbound

This paper cites Scaling laws for educational AI agents.

The Scaling Laws of Skills in LLM Agent Systems Scaling laws for educational AI agents

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-20T18:13:37.598661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:a96efbc0fbe51f6910c15cdfc6519363db8d6988cee4243c2fd91ab72fa78299

Observation b1a94159-c4d0-4ffd-93f6-104ebf28ff1e · outbound

This paper cites Dense passage retrieval for open-domain question answering.

The Scaling Laws of Skills in LLM Agent Systems Dense passage retrieval for open-domain question answering

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.240609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:b3d6bb094fbcc4b9e896e7aee698e9673c99b754ae91325ff586088ddbd38499

Observation f1d344b9-d06e-41cb-a80d-1fd9dee40865 · outbound

This paper cites Retrieval-augmented generation for knowledge- intensive NLP tasks.

The Scaling Laws of Skills in LLM Agent Systems Retrieval-augmented generation for knowledge- intensive NLP tasks

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.246227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:fa11e80dbc78067637ae8a803f00f3a93ac45474fa0421272212b367eae5257f

Observation 623f91e8-aa85-4a1e-8c7b-d7d4ab34aed5 · outbound

This paper cites Sentence-BERT: Sentence embeddings using siamese BERT-networks.

The Scaling Laws of Skills in LLM Agent Systems Sentence-BERT: Sentence embeddings using siamese BERT-networks

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.232935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:832cffa5355fb68fbf57c1b2204d45d119fb2c93901b3129a4ec2b07c2a50706

Observation 6babd043-5653-4fc4-82ad-9f81d777b3dc · outbound

This paper cites MTEB: Massive text embedding benchmark.

The Scaling Laws of Skills in LLM Agent Systems MTEB: Massive text embedding benchmark

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.230736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:d30b27972bf36c74f4aef4270bbda1ab756fc2f693d2f4bd1f8d76b86cee14f0

Observation 85e7fcab-81eb-48fd-901d-18349d0b4dfc · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.248575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:1f83c6b51e1b523e688f61aafeec8e9213d175c271bfde5d16ed362258ec70ae

Observation de0bb1ca-fa05-4b2b-8f5f-ee215a147414 · outbound

This paper cites Stimulus information as a determinant of reaction time.Journal of Experimental Psychology, 45 (3):188–196.

The Scaling Laws of Skills in LLM Agent Systems Stimulus information as a determinant of reaction time.Journal of Experimental Psychology, 45 (3):188–196

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.253362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:b848e383e1f22ab5461f2ea1819781909b261b54f6eaedc2df41f5460e20e761

Observation ad4f22ab-c08d-4694-aa1c-719cf0734ea8 · outbound

This paper cites Github - anthropics/skills: Public repository for agent skills.

The Scaling Laws of Skills in LLM Agent Systems Github - anthropics/skills: Public repository for agent skills

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.257862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f8eb482eebeca5138d2f4f1e8453acbf2c0a15c367cd30aa1acd3b792469e90b

Observation 1f5318dd-30e4-4db9-8941-316b6cc2536a · outbound

This paper cites Claude code.

The Scaling Laws of Skills in LLM Agent Systems Claude code

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.250749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:1866534538b69640b91a12d734f3e35234c8e2f009a22bc9bdc51e8b4fefe1b2

Observation abf0e788-d4ee-454f-8444-a3de8399d5ea · outbound

This paper cites Introducing the model context protocol.

The Scaling Laws of Skills in LLM Agent Systems Introducing the model context protocol

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.221149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:4f523a3013acc27b639f21f7184cf23bce3230af17a40424d358f9b80c5323dc

Observation e8c64544-c4cd-4803-bbb7-3067e8b0b6e1 · outbound

This paper cites Github - trailofbits/skills: Trail of bits claude code skills for security research, vulnerability detection, and audit workflows.https://github.com/trailofbits/skills.

The Scaling Laws of Skills in LLM Agent Systems Github - trailofbits/skills: Trail of bits claude code skills for security research, vulnerability detection, and audit workflows.https://github.com/trailofbits/skills

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.243888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:34da456e61ae81d07b67a81318b97a80b50358c9f9a52eedc41c4edea4bb0588

Observation 50bc34b6-e824-4d98-a0c8-ba3637ff9c04 · outbound

This paper cites Claude code skills marketplace.

The Scaling Laws of Skills in LLM Agent Systems Claude code skills marketplace

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.235760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:93f7e9eb24e5143dfd925e49b2515ca313afa4f506d4d8cbbd30281155870a83

Observation bb6ddbdb-08f5-45ff-b564-038926f53e60 · outbound

This paper cites NET skills for claude code.

The Scaling Laws of Skills in LLM Agent Systems NET skills for claude code

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.216437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:5a4b53c5e579148c9be3767a5dcf6c52dee1ef2a02011a589e85c1055368bc5a

Observation 24958d9a-5956-44da-88dd-fa604ff36986 · outbound

This paper cites PinchBench github organization.

The Scaling Laws of Skills in LLM Agent Systems PinchBench github organization

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.260225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:52176d1fa8a1bc8dcd3a86be6f530c0961baf425287e12ee50a745a594417573

Observation 9fb99964-a71d-4b50-8cc8-63f9e052b153 · outbound

This paper cites Agentdeals.https://github.com/robhunter/agentdeals.

The Scaling Laws of Skills in LLM Agent Systems Agentdeals.https://github.com/robhunter/agentdeals

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.265567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:50aae8255303bc96263eec9febfc27e17d438907ad5d3b74f99dea3fc8b73e00

Observation a5f69340-c7f3-41d2-b18d-8e903bb65f94 · outbound

This paper cites Unveiling the achilles’ heel of NLG evaluators: A unified adversarial framework driven by large language models.

The Scaling Laws of Skills in LLM Agent Systems Unveiling the achilles’ heel of NLG evaluators: A unified adversarial framework driven by large language models

Reference 54

Resolution
metadata mismatch
doi, observed 2026-05-20T18:13:37.085168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:cd3154c96fef587af2c471af663148809d6c4e6a616fe156da133960615ecb5e

Observation 9e6a24c5-3ac4-480e-8783-365692c34df5 · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.268127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:cfb67ed31e8833cc12a0d5b1d012ee23422c7e298949ebbc2dc348813e3ef0bb

Observation 27abc1ab-56ef-4fc6-9416-469e0595125f · outbound

This paper cites Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces.

The Scaling Laws of Skills in LLM Agent Systems Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.642484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:b752efc9a84345390f8d7db7d7d14aecdb3ca034538f9051105a69cfde87d458

Observation db4e3367-6b44-43cd-ab34-54ed1b4356bd · outbound

This paper cites $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains.

The Scaling Laws of Skills in LLM Agent Systems $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.575455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f6b4166693e85bc9cfdf0e7e098b2b426c0bde8c0d4329fa68b053a97e3cf855

Observation 88f97489-e255-4f18-8959-5dbf5adf40a3 · outbound

This paper cites $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment.

The Scaling Laws of Skills in LLM Agent Systems $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.639254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f5b01848df1c84e854bd073bbbde4b9031d068508309ecd7aa7e9df250f32a52

Observation 8b6a9c28-a446-4e9c-884d-9b397b83e473 · outbound

This paper cites Flow- Bench: Revisiting and benchmarking workflow-guided planning for LLM-based agents.

The Scaling Laws of Skills in LLM Agent Systems Flow- Bench: Revisiting and benchmarking workflow-guided planning for LLM-based agents

Reference 59

Resolution
verified exact
doi, observed 2026-05-20T18:13:37.087183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:421598a20b2255a1e69aaf3cc2707c09c15022306b365d2526c2831853588232

Observation a5ff57a2-6007-4cf6-aec0-a410502dbad7 · outbound

This paper cites Gpt-4o mini: advancing cost-efficient intelligence.

The Scaling Laws of Skills in LLM Agent Systems Gpt-4o mini: advancing cost-efficient intelligence

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.194716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:161675bc25b175f2c818afb803ec84a6742b82f7d351922e56a6d21bca0ce0b7

Observation d486fc9c-3629-4037-a51a-0af627bc7bc0 · outbound

This paper cites Gpt-5 system card.

The Scaling Laws of Skills in LLM Agent Systems Gpt-5 system card

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.211485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:6a0dcd087f278f5a2babc964b386685b428bb7339a71fbbb48077e297ac93b29

Observation f191868c-a939-4d99-a75f-5ef4f32e4f88 · outbound

This paper cites Introducing gpt-5.4 mini and nano.

The Scaling Laws of Skills in LLM Agent Systems Introducing gpt-5.4 mini and nano

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.203739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:f99c19c30b2e1585f2149d22c0674a4077fe2c21c1469773334c6ad844fe6db8

Observation 08d93b34-b314-496e-bbe7-a736490dea98 · outbound

This paper cites Introducing gpt-5.4.https://openai.com/index/introducing-gpt-5-4/.

The Scaling Laws of Skills in LLM Agent Systems Introducing gpt-5.4.https://openai.com/index/introducing-gpt-5-4/

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.195415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:db2349c82d8e0f4717c418a8b9c594a405660e9752db101788f90c3b676b87ea

Observation 1c730a86-9690-4a6e-be7c-5f12f123921d · outbound

This paper cites Introducing claude sonnet 4.6.https://www.anthropic.com/news/claude-sonnet-4-6.

The Scaling Laws of Skills in LLM Agent Systems Introducing claude sonnet 4.6.https://www.anthropic.com/news/claude-sonnet-4-6

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.198151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:418ba7c977eee2170487327af92d86f6ecb0653d1085358987fd82d2db643232

Observation ffb68d1a-32c6-4a61-97a6-0d05612421c9 · outbound

This paper cites Introducing claude opus 4.6.https://www.anthropic.com/news/claude-opus-4-6.

The Scaling Laws of Skills in LLM Agent Systems Introducing claude opus 4.6.https://www.anthropic.com/news/claude-opus-4-6

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.201005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:37daf917bff501b85f4fde85ad3a5c8bcbb5262942076918b0ea42d0a7048b2e

Observation 80ee954f-0a5e-47d6-9916-2e53a96b9a0b · outbound

This paper cites Gemini 3.Google DeepMind.

The Scaling Laws of Skills in LLM Agent Systems Gemini 3.Google DeepMind

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.209116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:485e6763ce2401060f49901875539503774618195e5296aa7d6e3f497cf1ab8b

Observation 798f9903-e3e7-4257-baee-04b10015b933 · outbound

This paper cites Glm-5: from vibe coding to agentic engineering.

The Scaling Laws of Skills in LLM Agent Systems Glm-5: from vibe coding to agentic engineering

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.214142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:646f2160f910f46eefe155457b31d6eaf16e8167181a59ae046daddb89c38ed1

Observation d80d842a-66cc-49ef-9749-560f1554d69e · outbound

This paper cites Glm-4.7: Advancing the coding capability.https://z.ai/blog/glm-4.7.

The Scaling Laws of Skills in LLM Agent Systems Glm-4.7: Advancing the coding capability.https://z.ai/blog/glm-4.7

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.238203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:fa04d89af947c1bdc2335143ab0d432875844898dee9d3e309d383c193c314f4

Observation 935be88b-864d-422d-b5d0-7e33696e7d98 · outbound

This paper cites Kimi k2.5: Visual agentic intelligence.

The Scaling Laws of Skills in LLM Agent Systems Kimi k2.5: Visual agentic intelligence

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.206583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:3c4e6dcfc8d42b7b741d4fb425fec8f22ab3a168ca7832fbf01c51818b4aad39

Observation e682c445-8d03-4983-9461-670c5a163cfd · outbound

This paper cites Kimi k2.6: From code to creation, from one to many.

The Scaling Laws of Skills in LLM Agent Systems Kimi k2.6: From code to creation, from one to many

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.304353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:875c4635a751f2c4a8a394f3e3778cf4c73a969e0ca0aae4c20844e015bdd847

Observation 531d13e3-b094-491d-b70e-0631dc82ff80 · outbound

This paper cites Seed 2.0 official launch.

The Scaling Laws of Skills in LLM Agent Systems Seed 2.0 official launch

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.309422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:e30dd1a3cd5b26449b589dc318591999e529b4c1b90d4b99327de974b7916d2b

Observation 726f8561-63fa-459d-a937-bfdecee8eb81 · outbound

This paper cites Deepseek-v4:towards highly efficient million-token context intelligence.https://huggingface.

The Scaling Laws of Skills in LLM Agent Systems Deepseek-v4:towards highly efficient million-token context intelligence.https://huggingface

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.311781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:0914b6824d49b425323fb69f6fbb1d7b8ab0c86dc18920357ad6f5d54b1897f6

Observation e520c5c9-7539-4f4d-8389-72ac62df8ea0 · outbound

This paper cites Qwen3 Technical Report.

The Scaling Laws of Skills in LLM Agent Systems Qwen3 Technical Report

Reference 73

Resolution
verified exact
local_arxiv, observed 2026-05-20T18:13:37.578846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:cb74902d9c15e976bcc1f72ca3bbf081c92acb346a4a07e73497205478c21a7b

Observation a509f3e2-f887-48a8-819a-48d61f980115 · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.295211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:157cb3c0aff727f35c984405e952e7c943156f51cf9af3f7b02fc195dd5c489c

Observation 93abe91d-940e-48c4-8071-ae2951094038 · outbound

This paper cites This is the scale-free local-crowding condition tested by the CI and semantic-gap diagnostics.

The Scaling Laws of Skills in LLM Agent Systems This is the scale-free local-crowding condition tested by the CI and semantic-gap diagnostics

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.297981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:3f1c8b9aa7e88f615e0ab652c227394680d01bf56025aec6c49cec1afe4706b9

Observation 8046b567-327e-4158-97b7-6dc2ec6531cb · outbound

This paper cites Irrelevant distractors have negligi- ble𝑤𝑗; local near-misses dominate𝐶(𝑁).

The Scaling Laws of Skills in LLM Agent Systems Irrelevant distractors have negligi- ble𝑤𝑗; local near-misses dominate𝐶(𝑁)

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.262899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:4a36f0ee4a747a8f9fb8db93fcafed681b2e8516e6deb893f57bcf0420d06ecb

Observation b6cd39c7-039c-4c1d-9352-4f2a7144648d · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.290121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:335571837f9a15ab6f61505b4d83b97c95f63eebb291d9d8069612518b0cda45

Observation fa793c67-ce79-45da-a92c-8c59601846c6 · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 78

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.272735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:929d1e830e697c7d60f024b0300abb96c6cf684312b891e70d5d6641e391d88e

Observation 0e978ef2-c601-4986-b682-1253988ad9ac · outbound

This paper cites Lemma 1 (Clustered libraries imply logarithmic effective competition).Under Assumption 2, Assumption 3 follows with𝐶1 =𝜅.

The Scaling Laws of Skills in LLM Agent Systems Lemma 1 (Clustered libraries imply logarithmic effective competition).Under Assumption 2, Assumption 3 follows with𝐶1 =𝜅

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.238422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:bad083b3370ae964dbecd5d4f87db3a6ba2e11bb58f605e2f69db7061b94d08d

Observation d13d173d-450d-415e-8157-c0046fa7719b · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 80

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.292520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:7c7589c7b6875ed051a8d21625765ada0fd746967e3727d6929af0663b21915d

Observation 7a54cbee-b395-4c5b-a706-db2bf58b36d7 · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 81

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.255510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:83678ad65f76f0867ef954ba15963676579265add55503f366c692fad726ee81

Observation 49ae69a4-7701-4ec0-9d56-1a64ed1d3ea0 · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 82

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.287653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:35ba5c7e03e478eff01cce6c8060d5fe081356d4d53b3fe98d08a37554db6308

Observation fe97e713-6c7a-498e-b7d2-dad8b12059ad · outbound

This paper cites 6.Library relevance: at least one available skill is plausibly needed, even if the exact gold skill set is decided later.

The Scaling Laws of Skills in LLM Agent Systems 6.Library relevance: at least one available skill is plausibly needed, even if the exact gold skill set is decided later

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.301394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:3929033ce4507025d4e8c3ff22346d1db2fd7839734176d0ea0b589808f6b130

Observation f06e4022-c4fd-4f04-9cfc-ac24df31950a · outbound

This paper cites 8.Single coherent request: the task should not bundle unrelated goals that would naturally be separate tasks.

The Scaling Laws of Skills in LLM Agent Systems 8.Single coherent request: the task should not bundle unrelated goals that would naturally be separate tasks

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.314181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:65bbf60de831209e20376ac9d95dc19faa4ca8eec107376eb1bdd62eed2ed8d7

Observation ea213951-73c9-4ab6-997f-2b2a8bae75ca · outbound

This paper cites Single-step tasks.Assign a gold skill set𝐺.

The Scaling Laws of Skills in LLM Agent Systems Single-step tasks.Assign a gold skill set𝐺

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T18:13:38.280604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:858598d7cac64591a3f5b39b692832d3bf56397728384f23257a102c3a2e35bf

Observation 60af0fb9-8db1-42c8-a360-07d25718d53e · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.270326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:b2e1d46ef0ffa44cd49a1804335086bd7fe08b321c46b9dbee2e27101f6a7f5e

Observation ef8037e8-50f9-4da9-b161-e9b3e8ba9a0d · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.282987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:dc7e2058ca96984bc3963d434040eb136754c033afab3076f801d280ad4a5883

Observation bb792871-31bf-4b80-aa7f-09856c12af21 · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.285191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:bf86fb70b963d29360c1cbe1a228b9eab2346dedfa82cd9c19ac30ff702cf190

Observation e1fff68d-14c7-4f93-b681-8dd0f59a1a1e · outbound

This paper cites an unresolved cited work.

The Scaling Laws of Skills in LLM Agent Systems Unresolved cited work

Reference 89

Resolution
unresolved
raw_fallback, observed 2026-05-20T18:13:38.277741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:fe39bd625864aaff7672f9055b405b16abd2026420da8b0279ba50ffb58e3ecf

Observation bdd0e669-646b-4787-9f3f-5b71c2efa16b · outbound

This paper cites Boundary Rewrite.

The Scaling Laws of Skills in LLM Agent Systems Boundary Rewrite

Reference 90

Resolution
malformed identifier
raw_fallback, observed 2026-05-20T18:13:38.275399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T18:10:08.737710Z digest=sha256:5b00f84acf59535607a34f7330774f9ea3f2470ee5fb68c5b2316ff73b319f56

Pith citing papers

Observation c86f91a9-4cf6-4cde-9878-e31a3231639f · inbound

SkillCorpus: Consolidating and Evaluating the Open Skill Ecosystem for Real-World LLM Agents cites this paper.

SkillCorpus: Consolidating and Evaluating the Open Skill Ecosystem for Real-World LLM Agents The Scaling Laws of Skills in LLM Agent Systems

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-01T23:04:12.409948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:04:12.409948Z digest=sha256:a6eefa2484133ae5305a9f520333eafc734cd0781e56cf4681c5316561336c28

Observation 96ed7f44-2c24-422d-8223-c11ce5dd7aed · inbound

Rethinking Self-Evolution: A Constrained Exploration-Exploitation Process for Mitigating Skill Overfitting cites this paper.

Rethinking Self-Evolution: A Constrained Exploration-Exploitation Process for Mitigating Skill Overfitting The Scaling Laws of Skills in LLM Agent Systems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-01T11:46:01.048124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:46:01.048124Z digest=sha256:f5cebb7d160e9ad54dc23dca68319d37a6192a82736b42273623493b79e36083