Paper Citation Record · LEDGER

Self-Challenging Language Model Agents

As of 14 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 17 inbound Pith citation observations for arXiv:2506.01716.

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

pith.paper-citation-record.v1
2506.01716 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:40:59.083259Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:34:45.225752Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:40:08.275113Z

Reference resolution

63 of 63 outbound references displayed

verified exact0
verified fuzzy9
unresolved53
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44438846-9183-4610-90f0-7e593061c643 · outbound

This paper cites Digirl: Training in-the-wild device-control agents with autonomous reinforcement learning,.

Self-Challenging Language Model Agents Digirl: Training in-the-wild device-control agents with autonomous reinforcement learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:12.244449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4fcd1709-dd65-44fe-9aaf-d2c5432967d9 · outbound

This paper cites Digi-q: Learning q-value functions for training device-control agents, 2025.

Self-Challenging Language Model Agents Digi-q: Learning q-value functions for training device-control agents, 2025

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:11.710204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bbfc647f-825b-4944-83b2-87e8202bbfb5 · outbound

This paper cites Active learning of inverse models with intrinsically motivated goal exploration in robots.Robotics and Autonomous Systems, 61(1):49–73, January.

Self-Challenging Language Model Agents Active learning of inverse models with intrinsically motivated goal exploration in robots.Robotics and Autonomous Systems, 61(1):49–73, January

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:11.280110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 46d9604d-cec9-4ee1-a125-379e12100f72 · outbound

This paper cites Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.

Self-Challenging Language Model Agents Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:11.978479Z

Source-reported events for the cited work

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Observation 55271e5d-fbaa-47c6-af00-754928eef049 · outbound

This paper cites Augmenting Autotelic Agents with Large Language Models.

Self-Challenging Language Model Agents Augmenting Autotelic Agents with Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:11.995004Z

Source-reported events for the cited work

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Observation 3e308654-6358-4618-b627-6424c6b70c04 · outbound

This paper cites STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving.

Self-Challenging Language Model Agents STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.012166Z

Source-reported events for the cited work

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Observation e2e57cc7-d1e9-4b17-8f2a-79768333aacb · outbound

This paper cites OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code.

Self-Challenging Language Model Agents OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.036961Z

Source-reported events for the cited work

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Observation 84c72a2d-a0d9-4de3-813c-6a0277e8d042 · outbound

This paper cites StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models.

Self-Challenging Language Model Agents StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.061630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4140923c-5a01-4a12-8a70-8c059f3d40e8 · outbound

This paper cites WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models.

Self-Challenging Language Model Agents WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.096694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55458e07-f4f4-41b1-98ed-6a97190d5b90 · outbound

This paper cites OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization.

Self-Challenging Language Model Agents OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.120277Z

Source-reported events for the cited work

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Observation 7075c19d-3928-4696-92d9-216f700d1d63 · outbound

This paper cites AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation.

Self-Challenging Language Model Agents AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.166978Z

Source-reported events for the cited work

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Observation e5012d17-4c79-439e-902d-1f3c5defdb41 · outbound

This paper cites Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents.

Self-Challenging Language Model Agents Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.226948Z

Source-reported events for the cited work

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Observation 410f2c01-01f4-4f77-a7ff-0e1c58e280a3 · outbound

This paper cites VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models.

Self-Challenging Language Model Agents VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:12.312709Z

Source-reported events for the cited work

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Observation f0edaf56-ac88-469d-ab56-cbf610a6870a · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Self-Challenging Language Model Agents SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:23.082871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b43d03bc-307d-44df-902d-a0d13e9eb2c3 · outbound

This paper cites Code as Policies: Language Model Programs for Embodied Control.

Self-Challenging Language Model Agents Code as Policies: Language Model Programs for Embodied Control

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:23.397800Z

Source-reported events for the cited work

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Observation ab90699e-f496-42b9-bff5-e614f6818198 · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

Self-Challenging Language Model Agents AgentBench: Evaluating LLMs as Agents

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:23.658612Z

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Observation 8efe4362-c272-49f6-b02d-572875a7f6a5 · outbound

This paper cites Toolverifier: Generalization to new tools via self-verification,.

Self-Challenging Language Model Agents Toolverifier: Generalization to new tools via self-verification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:10.860546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8509d31a-19ea-4514-b398-4b1ab50c565b · outbound

This paper cites BAGEL: Bootstrapping Agents by Guiding Exploration with Language.

Self-Challenging Language Model Agents BAGEL: Bootstrapping Agents by Guiding Exploration with Language

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:32.879610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35fe6451-5425-4df8-8a1d-3c4c4b110d75 · outbound

This paper cites NNetNav: Unsupervised Learning of Browser Agents Through Environment Interaction in the Wild.

Self-Challenging Language Model Agents NNetNav: Unsupervised Learning of Browser Agents Through Environment Interaction in the Wild

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:34.931028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 069c1569-803a-4f1a-985f-f97a6115f015 · outbound

This paper cites TOOLVERIFIER: Generalization to New Tools via Self-Verification.

Self-Challenging Language Model Agents TOOLVERIFIER: Generalization to New Tools via Self-Verification

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:31.436426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7a30c5e-1ac8-484e-8257-9319e44a419a · outbound

This paper cites Asymmetric self-play for automatic goal discovery in robotic manipulation.

Self-Challenging Language Model Agents Asymmetric self-play for automatic goal discovery in robotic manipulation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:35.884878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc14c05-cbd6-4278-9d8e-95b3dd20e67a · outbound

This paper cites Training Software Engineering Agents and Verifiers with SWE-Gym.

Self-Challenging Language Model Agents Training Software Engineering Agents and Verifiers with SWE-Gym

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:35.947084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e72e425-b329-461c-9199-90b445ef3a6c · outbound

This paper cites GPT-4 Technical Report.

Self-Challenging Language Model Agents GPT-4 Technical Report

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:35.724518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcba1132-d734-494e-be0a-fc5a787f1ed5 · outbound

This paper cites WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning.

Self-Challenging Language Model Agents WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:36.060344Z

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Observation bd9b4def-ad0f-4d5b-a55b-888658788f96 · outbound

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

Self-Challenging Language Model Agents ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:45.358026Z

Source-reported events for the cited work

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Observation 6dc74701-3f40-4066-a660-f5562c4d9d39 · outbound

This paper cites Autonomous Evaluation and Refinement of Digital Agents.

Self-Challenging Language Model Agents Autonomous Evaluation and Refinement of Digital Agents

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:36.023988Z

Source-reported events for the cited work

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Observation 28c6de98-65d2-48c1-919e-d9871dddb61f · outbound

This paper cites Toolformer: Language Models Can Teach Themselves to Use Tools.

Self-Challenging Language Model Agents Toolformer: Language Models Can Teach Themselves to Use Tools

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:55.541784Z

Source-reported events for the cited work

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Observation 423fe5aa-3fd5-4986-aa7a-15cc66178918 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Self-Challenging Language Model Agents Proximal Policy Optimization Algorithms

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:55.869742Z

Source-reported events for the cited work

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Observation 89d3f2f5-b7e7-477f-a571-cb0b6ec08b64 · outbound

This paper cites Manning, and Chelsea Finn.

Self-Challenging Language Model Agents Manning, and Chelsea Finn

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:53.228339Z

Source-reported events for the cited work

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Observation 9d9150a1-90bd-4f29-a1de-30872947537f · outbound

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

Self-Challenging Language Model Agents Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:54.882578Z

Source-reported events for the cited work

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Observation f77b4a4f-c468-4e2b-a958-4a503f82f586 · outbound

This paper cites Beyond Browsing: API-Based Web Agents.

Self-Challenging Language Model Agents Beyond Browsing: API-Based Web Agents

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:55.995454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba78255a-5eb4-47a1-95e4-33852fa53471 · outbound

This paper cites Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments.

Self-Challenging Language Model Agents Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:56.046550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dfb5f3c-33f7-400d-935a-6330fb4c0154 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Self-Challenging Language Model Agents DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:55.914021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bbadf7a-eb55-403f-ade2-fb13aff91af2 · outbound

This paper cites Tool Learning in the Wild: Empowering Language Models as Automatic Tool Agents.

Self-Challenging Language Model Agents Tool Learning in the Wild: Empowering Language Models as Automatic Tool Agents

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:55.929577Z

Source-reported events for the cited work

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Observation c56968f5-fefb-43bb-b764-1f379a84f427 · outbound

This paper cites AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents.

Self-Challenging Language Model Agents AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.755014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 668c004a-9259-4962-93a0-545038760051 · outbound

This paper cites DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agents.

Self-Challenging Language Model Agents DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agents

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.792768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d5913fc-de68-4b39-ab35-09770eacc699 · outbound

This paper cites Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play.

Self-Challenging Language Model Agents Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.515236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7944699a-559c-4c4d-bafc-ae724a4602e5 · outbound

This paper cites The llama 3 herd of models, 2024.

Self-Challenging Language Model Agents The llama 3 herd of models, 2024

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:10.502150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2e468fff-96e1-4eef-b693-be3b9530f842 · outbound

This paper cites Williams.

Self-Challenging Language Model Agents Williams

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:10.002527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1b6eaf50-65fe-4888-aeed-bbb2b5a13b0d · outbound

This paper cites TravelPlanner: A Benchmark for Real-World Planning with Language Agents.

Self-Challenging Language Model Agents TravelPlanner: A Benchmark for Real-World Planning with Language Agents

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.962659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cd74399-0b7b-453b-aa7f-aef601ca5057 · outbound

This paper cites Executable code actions elicit better llm agents, 2024.

Self-Challenging Language Model Agents Executable code actions elicit better llm agents, 2024

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:10.221816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 54afcc56-60f7-46b8-b56a-0a1e403c9161 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Self-Challenging Language Model Agents Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.896022Z

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Observation 9d4610b9-1bc1-40d5-a38a-0a7037f0988b · outbound

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

Self-Challenging Language Model Agents TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.089452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73a172da-00aa-4749-86ca-5381f9f6f256 · outbound

This paper cites Fung, Sha Li, Zixuan Huang, Xu Cao, Xingyao Wang, Yiquan Wang, Heng Ji, and Chengxiang Zhai.

Self-Challenging Language Model Agents Fung, Sha Li, Zixuan Huang, Xu Cao, Xingyao Wang, Yiquan Wang, Heng Ji, and Chengxiang Zhai

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:09.757374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e54719fc-d061-4af5-b4c3-0d10d14eea7c · outbound

This paper cites OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments.

Self-Challenging Language Model Agents OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.052425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a663a407-f076-41a0-aa8d-4a3156ce8dff · outbound

This paper cites Building Math Agents with Multi-Turn Iterative Preference Learning.

Self-Challenging Language Model Agents Building Math Agents with Multi-Turn Iterative Preference Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.073304Z

Source-reported events for the cited work

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Observation 9b24f184-baf4-4673-852c-2dfb7273c58f · outbound

This paper cites Self-Rewarding Language Models.

Self-Challenging Language Model Agents Self-Rewarding Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.356648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10aa5b6b-5496-4ae2-9d7a-4ee6d4e62532 · outbound

This paper cites OMNI: Open-endedness via Models of human Notions of Interestingness.

Self-Challenging Language Model Agents OMNI: Open-endedness via Models of human Notions of Interestingness

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.439810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 152db4ab-e76c-4598-830a-565b6c63cde2 · outbound

This paper cites If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents.

Self-Challenging Language Model Agents If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.149818Z

Source-reported events for the cited work

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Observation 9200b938-1689-4bd8-9392-2c18140e93c8 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Self-Challenging Language Model Agents ReAct: Synergizing Reasoning and Acting in Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.217468Z

Source-reported events for the cited work

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Observation 8266c9a7-a113-45a3-ae5c-aa8a09a141f8 · outbound

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

Self-Challenging Language Model Agents $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.289141Z

Source-reported events for the cited work

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Observation fe81ee85-bce5-4ea0-9666-744b80f639c5 · outbound

This paper cites ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL.

Self-Challenging Language Model Agents ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.654310Z

Source-reported events for the cited work

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Observation 17e33e8c-9b01-4cc9-a34c-5da8a28ac835 · outbound

This paper cites SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks.

Self-Challenging Language Model Agents SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.657810Z

Source-reported events for the cited work

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Observation a6de11e5-b574-4e06-9e1a-5db9438d4c39 · outbound

This paper cites Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

Self-Challenging Language Model Agents Absolute Zero: Reinforced Self-play Reasoning with Zero Data

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.509212Z

Source-reported events for the cited work

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Observation 04cc2d64-6626-4b19-9581-e619b5c30386 · outbound

This paper cites WebArena: A Realistic Web Environment for Building Autonomous Agents.

Self-Challenging Language Model Agents WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.622639Z

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Observation b86ca1b9-160a-4040-a855-44640c0293b4 · outbound

This paper cites Proposer-Agent-Evaluator(PAE): Autonomous Skill Discovery For Foundation Model Internet Agents.

Self-Challenging Language Model Agents Proposer-Agent-Evaluator(PAE): Autonomous Skill Discovery For Foundation Model Internet Agents

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:58.649855Z

Source-reported events for the cited work

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Observation ce4b2e87-9041-4d54-8d72-75dbd4fe54dc · outbound

This paper cites book_hotel.

Self-Challenging Language Model Agents book_hotel

Reference 59

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T11:41:09.532150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ea84a94d-1271-4b97-9f62-71d004797953 · outbound

This paper cites an unresolved cited work.

Self-Challenging Language Model Agents Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:41:09.288693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation de108500-ab37-433a-90e3-c454647d5249 · outbound

This paper cites an unresolved cited work.

Self-Challenging Language Model Agents Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:41:08.735978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1ba7cca5-8bda-48e2-bed5-bc982210b34e · outbound

This paper cites an unresolved cited work.

Self-Challenging Language Model Agents Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:40:59.913561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 868d2b48-4c99-48ab-b1dc-0a5d626a1325 · outbound

This paper cites order by mistake.

Self-Challenging Language Model Agents order by mistake

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:59.733589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 38b1a9f2-cdfd-41b1-aa91-b4e89a113c30 · outbound

This paper cites doi: 10.1016/j.robot.2012.05.008.

Self-Challenging Language Model Agents doi: 10.1016/j.robot.2012.05.008

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:11.955244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7c33ebd-f11e-44f7-a256-d7d3f4bfdf96 · outbound

This paper cites DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning.

Self-Challenging Language Model Agents DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:11.634772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 8c8e5dff-a1bb-4d5b-9570-67e5ef85cc2b · inbound

A Survey on Autonomy-Induced Security Risks in Large Model-Based Agents cites this paper.

A Survey on Autonomy-Induced Security Risks in Large Model-Based Agents Self-Challenging Language Model Agents

Reference 162

Resolution: unresolved; no resolver link, observed 2026-08-06T21:34:45.225752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9b936a2-fdb3-4a97-83f4-d8fb2ad1bedd · inbound

On the Surprising Efficacy of LLMs for Penetration-Testing cites this paper.

On the Surprising Efficacy of LLMs for Penetration-Testing Self-Challenging Language Model Agents

Reference 123

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:06.741227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44909370-f083-47e1-ba86-69cc313916ef · inbound

EvoCurr: Self-evolving Curriculum with Behavior Code Generation for Complex Decision-making cites this paper.

EvoCurr: Self-evolving Curriculum with Behavior Code Generation for Complex Decision-making Self-Challenging Language Model Agents

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T21:01:24.837854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0919db2c-5c8f-4623-b730-30bdc51d60f7 · inbound

A global log for medical AI cites this paper.

A global log for medical AI Self-Challenging Language Model Agents

Reference 124

Resolution: unresolved; no resolver link, observed 2026-08-04T11:34:15.689366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76755336-f839-4dc1-9ff6-32b58057e22b · inbound

Agent Learning via Early Experience cites this paper.

Agent Learning via Early Experience Self-Challenging Language Model Agents

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-04T10:48:06.257869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Help Without Being Asked: A Deployed Proactive Agent System for On-Call Support with Continuous Self-Improvement cites this paper.

Help Without Being Asked: A Deployed Proactive Agent System for On-Call Support with Continuous Self-Improvement Self-Challenging Language Model Agents

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:56:33.422593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c40d748a-1a6a-45f1-b923-dca4511200a7 · inbound

Training LLM Agents for Spontaneous, Reward-Free Self-Evolution via World Knowledge Exploration cites this paper.

Training LLM Agents for Spontaneous, Reward-Free Self-Evolution via World Knowledge Exploration Self-Challenging Language Model Agents

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:10:23.528665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ec11e069-6aa6-4de0-9353-d988fd8028ef · inbound

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Bootstrapping Post-training Signals for Open-ended Tasks via Rubric-based Self-play on Pre-training Text Self-Challenging Language Model Agents

Reference 50

Resolution: malformed identifier; arxiv_id, observed 2026-05-11T13:21:15.160379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6a93fdf-ad16-42ef-be51-5363fbcb7baa · inbound

G-Zero: Self-Play for Open-Ended Generation from Zero Data cites this paper.

G-Zero: Self-Play for Open-Ended Generation from Zero Data Self-Challenging Language Model Agents

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:11:24.540151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bc6d68ac-dd6b-428c-8fd6-2d9f97ce6bfc · inbound

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unix-ctf: Procedural Environments for Unix-Competence Reinforcement Learning Self-Challenging Language Model Agents

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T11:23:20.889344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 75264551-f090-40b5-8889-1034574942d0 · inbound

BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution cites this paper.

BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution Self-Challenging Language Model Agents

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:36:14.692118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bbab49ce-fdad-41c3-8d4e-f97b020e41b5 · inbound

SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents cites this paper.

SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents Self-Challenging Language Model Agents

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:33.158166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 690af5de-7de2-4896-8668-b5dddf254573 · inbound

PROTON: Prototype-Based Test-Time Online OOD Detection for Medical VLMs cites this paper.

PROTON: Prototype-Based Test-Time Online OOD Detection for Medical VLMs Self-Challenging Language Model Agents

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:39:30.510413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b43cfd81-e61e-4f3d-b85d-9e7af405a657 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data Self-Challenging Language Model Agents

Reference 125

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:40:08.276542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 63012396-d1c7-464f-ba22-ff404ea41de7 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data Self-Challenging Language Model Agents

Reference 125

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:19:51.230606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 876aefd1-24ed-4b36-9741-cf7d9a18fa55 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data Self-Challenging Language Model Agents

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-12T12:08:06.206832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27bf22bf-c004-4295-b46e-018c7c847b7b · inbound

Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning cites this paper.

Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning Self-Challenging Language Model Agents

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T18:35:58.476165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.