The Year in AI Papers
The year/Topics/Research automation

Research collection

Research automation

Automating the research workflow itself: paper writing and review assistance, literature synthesis, and paper-to-artifact generation.

Papers
13
Research labs
2
Official code
12

1–13 of 13 papers in this collection

01

Independent research

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement

The paper introduces Arbor, a general framework for autonomous research under the Autonomous Optimization (AO) setting, where an agent iteratively improves an initial artifact without step-level human supervision. Arbor uses Hypothesis Tree Refinement (HTR), combining a long-lived coordinator that maintains a persistent hypothesis tree (linking hypotheses,…

Jiajie Jin, Yuyang Hu, Kai Qiu, Qi Dai, et al.
Published
Jun 2026
Citations
2
Code
993 stars
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02

arXiv.org

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

AutoResearchClaw is a multi-agent autonomous research pipeline that addresses three key challenges in scientific discovery: hypothesis quality, execution robustness, and experience accumulation. It integrates five mechanisms: structured multi-agent debate for hypothesis generation and result analysis, a self-healing executor with a Pivot/Refine loop,…

Jiaqi Liu, Shi Qiu, Mairui Li, Bingzhou Li, et al.
Published
May 2026
Citations
13
Code
14K stars
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03

arXiv.org

AI for Auto-Research: Roadmap & User Guide

This paper surveys AI-assisted research across the complete academic lifecycle, organized into four phases (Creation, Writing, Validation, Dissemination) and eight stages. It finds that AI excels at structured, retrieval-grounded tasks but remains unreliable for novel ideas, research-level experiments, and scientific judgment. Key findings include:…

Lingdong Kong, Xian Sun, Wei Chow, Linfeng Li, et al.
Published
May 2026
Citations
5
Code
473 stars
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04

arXiv.org

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

ARIS is an open-source research harness for autonomous ML research, built on the assumption that single-agent long-horizon tasks are unreliable. It uses cross-model adversarial collaboration: an executor model (e.g., Claude) drives progress while a reviewer from a different model family (e.g., GPT-5.4) critiques artifacts and requests revisions. The system…

Ruofeng Yang, Yongcan Li, Shuai Li
Published
May 2026
Citations
9
Code
14K stars
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05

arXiv.org

Towards a Medical AI Scientist

The paper introduces Medical AI Scientist, the first autonomous research framework tailored to clinical medicine. It generates clinically grounded ideas by transforming surveyed literature into actionable evidence via a clinician-engineer co-reasoning mechanism, and drafts evidence-grounded manuscripts following a structured medical writing paradigm and…

Hongtao Wu, Boyun Zheng, Dingjie Song, Yu Jiang, et al.
Published
Mar 2026
Citations
4
Code
Not linked
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06

Independent research

InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery

InternAgent-1.5 is a unified agentic framework for long-horizon autonomous scientific discovery, developed by the InternScience Team at Shanghai Artificial Intelligence Laboratory. It addresses limitations of existing AI Scientist systems, such as domain-specific designs and limited long-horizon operation, by integrating three coordinated subsystems:…

Shiyang Feng, Runmin Ma, Xiangchao Yan, Yue Fan, et al.
Published
Feb 2026
Citations
20
Code
1.4K stars
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07

Meta AI

AIRS-Bench: a Suite of Tasks for Frontier AI Research Science Agents

AIRS-Bench is a benchmark suite of 20 tasks sourced from 17 state-of-the-art machine learning papers, designed to evaluate LLM agents on the full research lifecycle (idea generation, implementation, experimentation, analysis) without providing baseline code. Tasks span seven categories: language modeling, math, code, molecules/proteins, time series, text…

Alisia Lupidi, Bhavul Gauri, Thomas Simon Foster, Bassel Al Omari, et al.
Published
Feb 2026
Citations
14
Code
106 stars
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08

Google DeepMind

PaperBanana: Automating Academic Illustration for AI Scientists

PaperBanana is an agentic framework that automates the generation of publication-ready academic illustrations, such as methodology diagrams and statistical plots. It uses five specialized agents—Retriever, Planner, Stylist, Visualizer, and Critic—powered by VLMs and image generation models. The Retriever selects relevant reference examples, the Planner…

Dawei Zhu, Rui Meng, Yale Song, Xiyu Wei, et al.
Published
Jan 2026
Citations
19
Code
6.9K stars
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09

arXiv.org

Idea2Story: An Automated Pipeline for Transforming Research Concepts into Complete Scientific Narratives

Idea2Story is a framework for autonomous scientific discovery that shifts literature understanding from online reasoning to offline knowledge construction. It builds a structured methodological knowledge graph from peer-reviewed papers (about 13,000 from NeurIPS and ICLR over three years) and their review feedback, extracting reusable method units and…

Tengyue Xu, Zhuoyang Qian, Gaoge Liu, Li Ling, et al.
Published
Jan 2026
Citations
5
Code
1.4K stars
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10

Volume 1

Paper2Rebuttal: A Multi-Agent Framework for Transparent Author Response Assistance

The paper introduces REBUTTALAGENT, a multi-agent framework for assisting authors in writing peer-review rebuttals. It reframes rebuttal generation as an evidence-centric planning task, decomposing feedback into atomic concerns, constructing hybrid contexts from compressed and raw manuscript text, and integrating on-demand external literature search. The…

Qianli Ma, Chang Guo, Zhiheng Tian, Siyu Wang, et al.
Published
Jan 2026
Citations
6
Code
553 stars
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11

arXiv.org

GigaEvo: An Open Source Optimization Framework Powered By LLMs And Evolution Algorithms

GigaEvo is an open-source framework for LLM-driven evolutionary computation, inspired by AlphaEvolve, designed to enhance reproducibility and experimentation. It features modular components: a Redis-based storage for evolutionary units, an asyncio DAG execution engine, a MAP-Elites quality-diversity algorithm with single- and multi-island support, and a…

Valentin Khrulkov, Andrey Galichin, Denis Bashkirov, Dmitry Vinichenko, et al.
Published
Nov 2025
Citations
13
Code
125 stars
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12

arXiv.org

AutoPR: Let's Automate Your Academic Promotion!

The paper introduces AutoPR, a novel task for automatically generating promotional content from academic papers, along with PRBench, a benchmark of 512 paper-post pairs, and PRAgent, a multi-agent framework. PRAgent operates in three stages: content extraction, multi-agent synthesis, and platform-specific adaptation. Evaluations on PRBench show PRAgent…

Qiguang Chen, Zheng Yan, Mingda Yang, Libo Qin, et al.
Published
Oct 2025
Citations
4
Code
103 stars
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13

arXiv.org

ReviewScore: Misinformed Peer Review Detection with Large Language Models

The paper introduces REVIEWSCORE, a metric to detect misinformed review points in peer reviews, defined as questions answerable by the paper or weaknesses with incorrect premises. Human annotation of ICLR reviews found 15.2% of weaknesses and 26.4% of questions misinformed. The authors propose an automatic argument reconstruction engine that extracts…

Hyun Ryu, Doohyuk Jang, Hyemin S. Lee, Joonhyun Jeong, et al.
Published
Sep 2025
Citations
2
Code
0 stars
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