AI Paper Atlas

Research map / Multi-agent systems and games / LLM agents

Agent data synthesis and behavior studies

Synthesizes agent training data and examines behavioral biases in interactive LLM agents.

108 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2024–2026) · an approach in LLM agents, keyword cluster “gui · bench · software”

State History Tried Checklist Preprints Who Export

Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

8 papers in 2023–24 and 100 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 12.3% to 8.6%.

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

2016: 0162017: 0172018: 0182019: 0192020: 0202021: 0212022: 0222023: 0232024: 8242025: 18252026: 8226

Most cited paper of each year

Earliest papers here

What has been tried

26 papers here report 282 measured changes (a component added, removed or swapped, compared with a baseline): helped 68%, no clear effect 4%, hurt 25%, mixed 2%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
add within-episode CVaR risk controlGOOG · CR %-1.461 -> 25.077HelpedFinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making (NeurIPS 2024 · 37 citations)
add misconception refutationBoolQ · accuracy.83±.013 -> .85±.012HelpedMulti-LLM Debate: Framework, Principals, and Interventions (NeurIPS 2024 · 23 citations)
add planning; parse the video subtitle into subtasks rather than feed the full subtitle to the ActorAssistGUI overall · success rate35.0 -> 46.0HelpedAssistGUI: Task-Oriented PC Graphical User Interface Automation (CVPR 2024 · 14 citations)
neuro-symbolic multi-agent framework with dynamic diagnosis tree (vs direct role-playing gpt-4o)Human evaluation · Professionalism / Similarity / Fluency (ii)Professionalism 8.6 vs 6.8; Similarity 8.8 vs 6.4; Fluency (ii) 7.6 vs 5.5HelpedMDD-5k: A New Diagnostic Conversation Dataset for Mental Disorders Synthesized via Neuro-Symbolic LLM Agents (AAAI 2025 · 12 citations)
Use online rather than offline rule managementALFWorld · success rate90.7 -> 97.4HelpedAutoManual: Constructing Instruction Manuals by LLM Agents via Interactive Environmental Learning (NeurIPS 2024 · 8 citations)
use Universal Block Parsing (UBP) instead of baseline block parsingMultimodal-Mind2Web · Ele.AccHelpedSpiritSight Agent: Advanced GUI Agent with One Look (CVPR 2025 · 3 citations)
Use state abstraction with direct generation and fewer top-ranked elements instead of MCQ with top-50 elementsMind2Web · success rate32%HelpedSynapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control (ICLR 2024 · 3 citations)
Adding a Judge that verifies new conditions before they enter the condition list (Judge rejects incorrect conditions)MATH algebra case study · qualitative correctness of condition listHelpedMACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems (NeurIPS 2024 · 3 citations)
Add text controlFilm clips test set · FAD0.319 -> 0.219HelpedFilmComposer: LLM-Driven Music Production for Silent Film Clips (CVPR 2025 · 2 citations)
add Feedback to MedChain-Agent without Feedback or MedCase-RAGMedChain · Average0.4341 -> 0.4692HelpedMedChain: Bridging the Gap Between LLM Agents and Clinical Practice with Interactive Sequence (NeurIPS 2025 · 2 citations)
use Bandit rather than random action selectionCSI300 · IC0.0445 -> 0.0532HelpedR&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization (NeurIPS 2025 · 1 citation)
Add the Perception AgentCora · accuracy88.5±0.8 -> 93.7±1.0HelpedGraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments (NeurIPS 2025 · 1 citation)

What reviewers will expect

Datasets and baselines named in the 100 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Datasets

  • HotpotQA · 3 of 100 papers
  • Natural Questions · 2 of 100 papers
  • Musique · 2 of 100 papers
  • MMLU · 2 of 100 papers
  • WebShop · 2 of 100 papers
  • MedQA · 2 of 100 papers
  • PubMedQA · 2 of 100 papers
  • PathVQA · 2 of 100 papers

Baselines

  • GPT-4o · 15 of 100 papers
  • DeepSeek-R1 · 6 of 100 papers
  • GPT-5 · 6 of 100 papers
  • Qwen3-32B · 5 of 100 papers
  • GPT-4o-mini · 5 of 100 papers
  • ReAct · 4 of 100 papers
  • Qwen3-8B · 4 of 100 papers
  • GPT-4.1 · 4 of 100 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 108 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 20 key papersOpen the topic in the interactive map

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    Same keyword cluster

    Elsewhere in the topic

    Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).

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