This paper presents Clarus, a collaboration infrastructure for coordinating autonomous research agents towards web-scale scientific collaboration.

This paper investigates the correlation between gender diversity and the scientific impact of papers in Natural Language Processing (NLP) and Library and Information Science (LIS) domains.

The paper introduces Science Earth, a planet-scale scientific runtime that enables diverse, siloed AI capabilities to connect and collaborate dynamically, demonstrating that scientific discovery can b…

The paper proposes a taxonomy for AI-human collaboration in scientific evaluation and introduces the Paper Assistant Tool (PAT) to accelerate verification and review process in scientific research.

This paper introduces Aleena, an open-source lifecycle alignment agent that uses GitHub to align research software engineering stakeholders and preserve decision continuity.

The paper proposes COWEAVER, a bidirectional, learnable and explainable algorithm for matching scientists and forming collaborations within a human-agent network.

This paper investigates the ability of large language models to assist in scientific project planning and proposal evaluation, finding that human reviewers rate human- and AI-written proposals similar…

The paper introduces 'Matter to Mechanism,' a novel benchmark designed to rigorously evaluate AI co-scientists' ability to generate plausible, mechanism-grounded solution hypotheses for complex materi…

AutoScientists introduces a decentralized, self-organizing team of AI agents that significantly improves long-running scientific experimentation by enabling parallel exploration and knowledge sharing.

AutoSci is a memory-centric agentic system designed to automate the entire scientific research lifecycle by integrating structured memory, multi-stage execution, and continuous self-improvement.

This paper introduces Agents-K1, an end-to-end knowledge orchestration pipeline that converts raw documents into agent-native scientific knowledge graphs.

PaperPilot is an interactive literature search agent that constructs an executable DAG of paper-search operators based on user queries and feedback, improving search results and reducing errors.

This survey provides a comprehensive analysis of Reasoning Language Model (RLM) adoption across 28 scientific disciplines, revealing significant disparities in RLM maturity across different scientific…

This paper presents a software ecosystem enabling consistent development environments for running workflows across diverse hardware platforms.

The paper introduces Crafter, a multi-agent harness that significantly improves the generation of editable, publication-quality scientific figures from diverse inputs, addressing the limitations of ex…

This paper systematically analyzes 2.7 million arXiv submissions to demonstrate that nearly every preprint unintentionally discloses sensitive or unnecessary information through its source files, prop…

The paper proposes using Trusted-Execution Environments (TEEs) to create a scalable, privacy-preserving system where authors can submit cryptographic proofs of correct research replication, thereby ad…

This paper introduces tap, a file-based collaboration protocol enabling LLM agents from different vendors to collaborate on a shared codebase without shared memory or identical runtimes.

The paper designs and evaluates a triadic LLM-Teacher collaboration system for K-12 writing, finding that strategic labor division between the LLM and teacher effectively improves writing quality but…