arXiv AI
Jun 29
The Shift Toward Open and Reproducible AI Research
arXiv:2606. 16974v3 Announce Type: replace Abstract: The reproducibility crisis has directed the AI research community toward improving documentation practices.
The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers
arXiv:2606. 16974v1 Announce Type: new Abstract: The reproducibility crisis has directed the AI research community toward improving documentation practices.
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arXiv AI
Jun 9
Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting
arXiv:2606. 09809v1 Announce Type: new Abstract: AI evaluation results are produced at scale but reported inconsistently across leaderboards, model cards, benchmark papers, and company blogs.
arXiv AI
Jun 11
Can AI Agents Synthesize Scientific Conclusions?
arXiv:2606. 11337v1 Announce Type: new Abstract: Scientific AI agents increasingly retrieve evidence, reason across sources, and synthesize conclusions used in consequential decisions.
arXiv AI
Jul 29
Measuring the State of Open Science in Transportation Using Large Language Models
arXiv:2601. 14429v2 Announce Type: replace-cross Abstract: Open science initiatives have strengthened scientific integrity and accelerated research progress across many fields, but the state of their practice within transportation research remains under-investigated.
Hugging Face Trending Papers
Jun 30
FARS: A Fully Automated Research System Deployed at Scale
Recent automated research systems show that language-model agents can generate hypotheses, run experiments, and write complete manuscripts, but most evidence still comes from selected examples, human-framed topics, or a few pre-defined research tasks. We present FARS (Fully Automated Research System), a fully automated AI-for-AI research system designed to operate across research topics at scale.
arXiv AI
Jul 1
FARS: A Fully Automated Research System Deployed at Scale
arXiv:2606. 31651v1 Announce Type: new Abstract: Recent automated research systems show that language-model agents can generate hypotheses, run experiments, and write complete manuscripts, but most evidence still comes from selected examples, human-framed topics, or a few pre-defined research tasks.
arXiv AI
Jun 9
Context Rot in AI-Assisted Software Development: Repurposing Documentation Consistency for AI Configuration Artifacts
arXiv:2606. 09090v1 Announce Type: cross Abstract: Developers increasingly provide AI coding assistants with persistent context through configuration files such as CLAUDE.
arXiv AI
Aug 3
Can AI Evaluate AI Scientists? A Benchmarking Study of Autonomous Research Generation Systems Using Automated Multi-Model Review
arXiv:2607. 28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery.
arXiv AI
Jun 29
Towards Automating Scientific Review with Google's Paper Assistant Tool
arXiv:2606. 28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem proving.
arXiv Machine Learning
Aug 4
Computational Approaches to Understanding Large Language Model Impact on Writing and Information Ecosystems
arXiv:2506. 17467v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society.
arXiv AI
Aug 5
AI-Assisted Peer Review Across Research Communities: From Reviewer AI Policies to LLM Review Quality
arXiv:2608. 03581v1 Announce Type: cross Abstract: AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are.
Hugging Face Trending Papers
Aug 4
AI-Assisted Peer Review Across Research Communities: From Reviewer AI Policies to LLM Review Quality
AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are. We address these questions by first surveying reviewer-facing AI policies across 111 leading AI/NLP conferences and medical journals, revealing substantial regulation differences between the two communities.