Paper Citation Record · LEDGER

Revisiting DAgger in the Era of LLM-Agents

As of 7 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2605.12913.

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

pith.paper-citation-record.v1
2605.12913 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-14T19:56:06.762156Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T17:03:13.686066Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

verified exact36
verified fuzzy15
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0f338167-c8d8-4dfb-8361-fcc3fd9d278f · outbound

This paper cites GPT-4 Technical Report.

Revisiting DAgger in the Era of LLM-Agents GPT-4 Technical Report

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.211035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0c3d0106-9ea7-4a48-9a11-affce4ab7d5a · outbound

This paper cites On-policy distillation of language models: Learning from self-generated mistakes.

Revisiting DAgger in the Era of LLM-Agents On-policy distillation of language models: Learning from self-generated mistakes

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:21.976243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 619dbdc9-3520-4728-8829-7cdc3964311c · outbound

This paper cites Dream: Deep research evaluation with agentic metrics.

Revisiting DAgger in the Era of LLM-Agents Dream: Deep research evaluation with agentic metrics

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.187522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cc2818dd-c3f1-4f69-9690-043a094e1c59 · outbound

This paper cites SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents.

Revisiting DAgger in the Era of LLM-Agents SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.174612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 06f21fcf-7552-41a3-9693-578dfdeeec95 · outbound

This paper cites Qwen3-Coder-Next Technical Report.

Revisiting DAgger in the Era of LLM-Agents Qwen3-Coder-Next Technical Report

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:12:48.468873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation da6d06d9-ae7e-4996-af0d-a2e2c1138b09 · outbound

This paper cites arXiv preprint arXiv:2511.16108(2025).

Revisiting DAgger in the Era of LLM-Agents arXiv preprint arXiv:2511.16108(2025)

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.202579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c23039ba-560c-4e0e-ba44-696fcf0d6fbf · outbound

This paper cites MARS: Modular Agent with Reflective Search for Automated AI Research.

Revisiting DAgger in the Era of LLM-Agents MARS: Modular Agent with Reflective Search for Automated AI Research

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-21T02:04:10.539767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b534405e-cd85-4345-be75-717472ff255e · outbound

This paper cites Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning.

Revisiting DAgger in the Era of LLM-Agents Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.313781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1f76ec03-8ca9-4350-9d84-e9bd18427348 · outbound

This paper cites BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent.

Revisiting DAgger in the Era of LLM-Agents BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.390539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation daeeb332-a50a-4ef3-a9f2-b377543fed49 · outbound

This paper cites Agentless: Demystifying LLM-based Software Engineering Agents.

Revisiting DAgger in the Era of LLM-Agents Agentless: Demystifying LLM-based Software Engineering Agents

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-05-14T19:57:53.362813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cb211981-c4ba-45fc-8e1c-144680c49ffb · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Revisiting DAgger in the Era of LLM-Agents Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.410083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c8ade44b-5959-4279-a90b-bffac6b7c730 · outbound

This paper cites SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?.

Revisiting DAgger in the Era of LLM-Agents SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.403116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9eb666c0-c41c-4e52-a503-419ec1963c9b · outbound

This paper cites MiniLLM: Knowledge distillation of large language models.

Revisiting DAgger in the Era of LLM-Agents MiniLLM: Knowledge distillation of large language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.023639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b8c2506-8401-4135-98f3-dcec997c47c8 · outbound

This paper cites Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains.

Revisiting DAgger in the Era of LLM-Agents Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.451850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aa436afe-a220-430c-b5b5-4fcee276890c · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Revisiting DAgger in the Era of LLM-Agents DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.320219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0cf73e6a-ab19-4c72-9a70-c6dab9e847e9 · outbound

This paper cites Large language models for software engineering: A systematic literature review.ACM Transactions on Software Engineering and Methodology, 33(8):1–79.

Revisiting DAgger in the Era of LLM-Agents Large language models for software engineering: A systematic literature review.ACM Transactions on Software Engineering and Methodology, 33(8):1–79

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.040932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4b40848d-8da1-4381-8ad0-214d3ede2699 · outbound

This paper cites Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents.

Revisiting DAgger in the Era of LLM-Agents Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.272134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 59767a69-7b2b-4992-b20a-9e1d77c95c1f · outbound

This paper cites Reinforcement Learning via Self-Distillation.

Revisiting DAgger in the Era of LLM-Agents Reinforcement Learning via Self-Distillation

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.445431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9561e11b-83d9-4b19-b87d-8b9f31164a68 · outbound

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

Revisiting DAgger in the Era of LLM-Agents SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.298149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d76b8ae0-45fe-4b66-90ca-308bec072607 · outbound

This paper cites arXiv preprint arXiv:2512.14895 , year=.

Revisiting DAgger in the Era of LLM-Agents arXiv preprint arXiv:2512.14895 , year=

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.194309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 260ee51f-7f7e-4ddd-b54b-6bd8aeabb2c5 · outbound

This paper cites Large Language Model-Based Agents for Software Engineering: A Survey.

Revisiting DAgger in the Era of LLM-Agents Large Language Model-Based Agents for Software Engineering: A Survey

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:35:49.024248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e9f924e2-7439-4608-9e75-431e6ff848a7 · outbound

This paper cites On-policy distillation.Thinking Machines Lab: Con- nectionism.

Revisiting DAgger in the Era of LLM-Agents On-policy distillation.Thinking Machines Lab: Con- nectionism

Reference 22

Resolution: verified exact; doi, observed 2026-05-14T19:57:52.351707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e3560fa6-2074-4060-b82b-87525a5b83d9 · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744.

Revisiting DAgger in the Era of LLM-Agents Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.027042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 527fa34d-1bb3-4629-b3ef-1c8ec9fccfc7 · outbound

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

Revisiting DAgger in the Era of LLM-Agents Training Software Engineering Agents and Verifiers with SWE-Gym

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:20:40.573423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c4716b66-c20c-4d60-8e79-4fd9745cbe2a · outbound

This paper cites MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering.

Revisiting DAgger in the Era of LLM-Agents MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:57:53.369729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7576f433-e031-40b6-9398-2cacf1c76b48 · outbound

This paper cites Mle-smith: Scaling mle tasks with automated multi-agent pipeline.

Revisiting DAgger in the Era of LLM-Agents Mle-smith: Scaling mle tasks with automated multi-agent pipeline

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.291793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation acf8cdbf-cc57-4916-b9d9-5dcbc17a9e7d · outbound

This paper cites Efficient reductions for imitation learning.

Revisiting DAgger in the Era of LLM-Agents Efficient reductions for imitation learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.030139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3bf08f22-8d83-49dd-b4ca-e8470761cfcc · outbound

This paper cites Reinforcement and Imitation Learning via Interactive No-Regret Learning.

Revisiting DAgger in the Era of LLM-Agents Reinforcement and Imitation Learning via Interactive No-Regret Learning

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.264138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5c454286-9ad8-45c8-9fc2-c8dcd10eaff8 · outbound

This paper cites A reduction of imitation learning and structured prediction to no-regret online learning.

Revisiting DAgger in the Era of LLM-Agents A reduction of imitation learning and structured prediction to no-regret online learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.003131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c16bdd4a-4ea6-4750-b0b3-029263b7e75c · outbound

This paper cites Proximal Policy Optimization Algorithms.

Revisiting DAgger in the Era of LLM-Agents Proximal Policy Optimization Algorithms

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.245712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36f185b7-b137-4671-bcb7-d0ea2bddae76 · outbound

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

Revisiting DAgger in the Era of LLM-Agents DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.439026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bd3ae417-308a-43ba-8ecd-d8b60f11a7b4 · outbound

This paper cites Swe-dev: Building software engineering agents with training and inference scaling.

Revisiting DAgger in the Era of LLM-Agents Swe-dev: Building software engineering agents with training and inference scaling

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.007279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3bce33c8-dbd1-4780-8f1f-25c47ea3b937 · outbound

This paper cites Software testing with large language models: Survey, landscape, and vision.IEEE Transactions on Software Engineering, 50(4):911–936.

Revisiting DAgger in the Era of LLM-Agents Software testing with large language models: Survey, landscape, and vision.IEEE Transactions on Software Engineering, 50(4):911–936

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.033420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 517b65a0-f006-47e5-ba07-366f717446b7 · outbound

This paper cites OpenHands: An Open Platform for AI Software Developers as Generalist Agents.

Revisiting DAgger in the Era of LLM-Agents OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.424827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ebc54fea-072f-45f2-809c-f51714c706d3 · outbound

This paper cites BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents.

Revisiting DAgger in the Era of LLM-Agents BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.327350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f6306b97-77aa-429b-a27a-88fbaa638f72 · outbound

This paper cites SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution.

Revisiting DAgger in the Era of LLM-Agents SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:27:56.991478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c46f3c3-6578-4e08-87cc-4480fa49308b · outbound

This paper cites Automated program repair in the era of large pre-trained language models.

Revisiting DAgger in the Era of LLM-Agents Automated program repair in the era of large pre-trained language models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.038515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a7d32c6-f7fc-4d5d-8f47-1eff2b7a0f04 · outbound

This paper cites Qwen3 Technical Report.

Revisiting DAgger in the Era of LLM-Agents Qwen3 Technical Report

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.235908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6bde1360-43e0-43e8-ad58-a28919fff1dc · outbound

This paper cites Swe-agent: Agent-computer interfaces enable automated software engineering.Advances in Neural Information Processing Systems, 37:50528–50652.

Revisiting DAgger in the Era of LLM-Agents Swe-agent: Agent-computer interfaces enable automated software engineering.Advances in Neural Information Processing Systems, 37:50528–50652

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.017613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9f97d393-789d-4cda-a4ec-5ba28789fa21 · outbound

This paper cites SWE-smith: Scaling Data for Software Engineering Agents.

Revisiting DAgger in the Era of LLM-Agents SWE-smith: Scaling Data for Software Engineering Agents

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:22:07.061654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 83d2cc52-cd90-48ae-a519-dba65306dc3c · outbound

This paper cites Reinforcement Learning for Machine Learning Engineering Agents.

Revisiting DAgger in the Era of LLM-Agents Reinforcement Learning for Machine Learning Engineering Agents

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.418198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6d9ae2b-fa2d-4991-95a4-32a88213f45b · outbound

This paper cites DCPO: Dynamic Clipping Policy Optimization.

Revisiting DAgger in the Era of LLM-Agents DCPO: Dynamic Clipping Policy Optimization

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.349495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7160c5ee-8e62-4740-b672-920004c215c2 · outbound

This paper cites Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT.

Revisiting DAgger in the Era of LLM-Agents Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.334730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation da1863f4-b4ff-4fdf-9bf7-023c4ad3ac75 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Revisiting DAgger in the Era of LLM-Agents DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.356182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 16874846-5b3e-4a1d-a01b-1d0c9fd2a6ca · outbound

This paper cites Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving.

Revisiting DAgger in the Era of LLM-Agents Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:48:50.578231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c02b3ea4-c9f0-4dd8-b92f-f1bd79cbaf88 · outbound

This paper cites type": "function.

Revisiting DAgger in the Era of LLM-Agents type": "function

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:57:53.376666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a44fc95-3095-400e-9128-f119bb5dce30 · outbound

This paper cites CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges.

Revisiting DAgger in the Era of LLM-Agents CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.228204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 897e6c6e-d49a-4d09-a7bf-331fe64c42af · outbound

This paper cites Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models.

Revisiting DAgger in the Era of LLM-Agents Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-14T19:57:53.432150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 70533bfb-237f-4ac6-8ece-62345060cbbb · outbound

This paper cites why is X happening.

Revisiting DAgger in the Era of LLM-Agents why is X happening

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.254003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7dbd8c85-e67c-49f8-8fe5-35813f1bb9ba · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:21.981784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0ef470e4-df71-4411-a6b3-2c90ebfc3d28 · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:21.999657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c6d5856-b5fe-4376-bba2-113e55cf9b85 · outbound

This paper cites * For new features: Consider test-driven development when appropriate.

Revisiting DAgger in the Era of LLM-Agents * For new features: Consider test-driven development when appropriate

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:21.984473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2f485735-736a-4d3c-bea6-e7866ff37ea8 · outbound

This paper cites * Always modify existing files directly rather than creating new versions with different suffixes.

Revisiting DAgger in the Era of LLM-Agents * Always modify existing files directly rather than creating new versions with different suffixes

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:21.994555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9aea05ad-2c89-44f0-9a11-da9e700f5985 · outbound

This paper cites If the environment is not set up to run tests, consult with the user first before investing time to run tests.

Revisiting DAgger in the Era of LLM-Agents If the environment is not set up to run tests, consult with the user first before investing time to run tests

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:21.978756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aeabb3c5-f9c5-40ee-8f7f-aa80a2375a39 · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:22.035833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 05a6a184-ed50-486e-ba9d-fb5a25a99587 · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:21.997213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f8b9512c-eb3a-4a4a-890f-1e144e86fbea · outbound

This paper cites * Similarly, if you encounter missing dependencies for essential tools requested by the user, install them when possible.

Revisiting DAgger in the Era of LLM-Agents * Similarly, if you encounter missing dependencies for essential tools requested by the user, install them when possible

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.010648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6981459f-cd26-40ba-aae3-c68def5a85fd · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:22.020652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 98163856-8160-487c-a09e-45806d96673e · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:21.988811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 13d66908-21cf-4e06-adc4-d96201bc8093 · outbound

This paper cites an unresolved cited work.

Revisiting DAgger in the Era of LLM-Agents Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-05-15T17:21:21.991673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b96d38d9-6fea-40ac-b09c-577ebd858a01 · outbound

This paper cites * When you run into any major issue while executing a plan from the user, please don’t try to directly work around it.

Revisiting DAgger in the Era of LLM-Agents * When you run into any major issue while executing a plan from the user, please don’t try to directly work around it

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T17:21:22.014342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 02d6f244-0343-4cbd-a70c-83666b5ff433 · inbound

A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training cites this paper.

A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training Revisiting DAgger in the Era of LLM-Agents

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-11T17:03:13.686066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.