mlsanityData to 14 Oct 2026

Dr. Claw: An AI Scientist Workspace for Vibe Research

arXiv 2609.00365 ↗First posted 31 Aug 2026cs.AI cs.CL cs.CVcited by 1

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, yet end-to-end research still fragments across chat tools, IDEs, terminals, and writing environments, and the decisions that make it auditable are rarely preserved. We present Dr. Claw, an open-source workspace that wraps existing coding-agent executors in a controllable and auditable human-in-the-loop workflow rather than introducing another autonomous agent. Persistent state objects, a reusable skill library, and multi-executor coordination link human decisions to AI execution, turning planning, execution, and writing into one traceable, recoverable loop. We demonstrate Dr. Claw through an interactive three-view scenario and a failure-recovery walkthrough, and evaluate it against a bare command-line agent sharing the same backend executor, so the comparison contrasts the whole orchestration layer (task graph, state objects, and skill library) with the agent it wraps. Holding the executor fixed, Dr. Claw scores higher on research completeness while persisting an auditable, recoverable process trail. Demo access: repository https://github.com/OpenLAIR/dr-claw, released under AGPL-3.0 with GPL-3.0 upstream components.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 22 of its 30 references that are in the map. First posted on arXiv 31 Aug 2026.

Builds on

22 of 30 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024AutoGen Studio: A No-Code Developer Tool for Building and Debugging Multi-Agent Systems9 Aug
  2. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation16 Aug
  3. 2023ChatDev: Communicative Agents for Software Development16 Jul

Other references · 19

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  4. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  5. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  6. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
  7. 2025Agent Laboratory: Using LLM Agents as Research Assistantscited by 425
  8. 2025The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Searchcited by 422
  9. 2022Grounded Copilot: How Programmers Interact with Code-Generating Modelscited by 218
  10. 2024ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Modelscited by 210
  11. 2022GitHub Copilot AI pair programmer: Asset or Liability?cited by 152
  12. 2024CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needscited by 84
7 more
  1. 2024WaitGPT: Monitoring and Steering Conversational LLM Agent in Data Analysis with On-the-Fly Code Visualizationcited by 39
  2. 2024Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decompositioncited by 29
  3. 2023How Do Analysts Understand and Verify AI-Assisted Data Analyses?cited by 26
  4. 2025IRIS: Interactive Research Ideation System for Accelerating Scientific Discoverycited by 19
  5. 2025TinyScientist: An Interactive, Extensible, and Controllable Framework for Building Research Agentscited by 8
  6. 2025The Impact of Generative AI Coding Assistants on Developers Who Are Visually Impairedcited by 7
  7. 2025ResearStudio: A Human-Intervenable Framework for Building Controllable Deep-Research Agentscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026The Agentic Scientist: Orchestrating Coding Agents for Automated Scientific (Co-)Discovery
  2. 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
  3. 2026Humans are Missing from AI Coding Agent Research
  4. 2026Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems
  5. 2026SWE-chat: Coding Agent Interactions From Real Users in the Wild
  6. 2026Do AI Coding Agents Log Like Humans? An Empirical Study
  7. 2026Scaling Human-AI Coding Collaboration Requires a Governable Consensus Layer
  8. 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gap