research papers
30 articles about research papers in AI news
Google's AutoWrite AI Generates Research Papers from Scratch
Google published a paper detailing AutoWrite, an AI system that can generate complete research papers from scratch. This represents a significant step toward automating the scientific writing process.
OpenAI Agents Now Ask Questions Good Enough for Research Papers
Sébastien Bubeck revealed on the OpenAI Podcast that internal AI agents now ask research questions so insightful they're inspiring papers and correcting published mistakes, with a 1-2 year timeline for full researcher-level capabilities.
Reproducibility Crisis in Graph-Based Recommender Systems Research: SIGIR 2022 Papers Under Scrutiny
A new study analyzing 10 graph-based recommender system papers from SIGIR 2022 finds widespread reproducibility issues, including data leakage, inconsistent artifacts, and questionable baseline comparisons. This calls into question the validity of reported state-of-the-art improvements.
Microsoft & CUHK Debut 'Medical AI Scientist' Agent That Generates Ideas, Runs Experiments, and Writes Papers
Microsoft Research and CUHK have developed an autonomous AI agent that can formulate research ideas, execute experiments, and author papers, achieving near-MICCAI quality on 171 clinical cases across 19 tasks.
GPT ImageGen-2 Passes 'Otter Test', Generates Academic Papers
Wharton professor Ethan Mollick reports OpenAI's GPT ImageGen-2 now reliably generates complex text within images, including academic papers and slides, marking a significant leap in multimodal AI capability.
Hugging Face OCRs 27,000 arXiv Papers to Markdown with Open 5B Model
Hugging Face CEO Clement Delangue announced the OCR conversion of 27,000 arXiv papers to Markdown using an open 5B-parameter model and 16 parallel jobs on L40S GPUs. This demonstrates a scalable, open-source pipeline for large-scale academic document processing.
PRL-Bench: LLMs Score Below 50% on End-to-End Physics Research Tasks
Researchers introduced PRL-Bench, a benchmark built from 100 recent Physical Review Letters papers, testing LLMs on end-to-end physics research. Top models scored below 50%, exposing a significant capability gap for autonomous scientific discovery.
Study of 42,000 AI Researchers Shows Industry Salaries Top $2M, Public Paper Output Plummets
A new study tracking 42,000 AI researchers found the top 1% in industry earn ~$2M annually. Upon moving to private companies, researchers file 530% more patents and drastically reduce publishing public papers.
Three Research Frontiers in Recommender Systems: From Agent-Driven Reports to Machine Unlearning and Token-Level Personalization
Three arXiv papers advance recommender systems: RecPilot proposes agent-generated research reports instead of item lists; ERASE establishes a practical benchmark for machine unlearning; PerContrast improves LLM personalization via token-level weighting. These address core UX, compliance, and personalization challenges.
AI Research Breakthroughs: From Video Reasoning to Self-Stopping Models
This week's top AI papers reveal major advances in video understanding, reasoning efficiency, and agent training. Researchers introduced a massive video reasoning dataset, models that know when to stop thinking, and techniques for improving AI agents without full retraining.
AI Researcher Automates Slide Decks from 1K+ Paper Wiki Using Gamma MCP
Omar S. automated the creation of slide presentations from a personal wiki of 1,000+ AI papers. The pipeline uses the Gamma MCP connector for Claude to generate polished decks on demand.
Omar Saadoun's PaperWiki AI Agents Now Generate Personalized Research Surveys
Omar Saadoun announced that his PaperWiki platform now uses AI agents to generate personalized survey papers from a user's LLM-generated knowledge base. These surveys are self-improving and update automatically as new papers are published.
Stanford & Princeton Launch 'Reproducibility Challenge' to Address AI Research Crisis
Stanford and Princeton are launching a challenge to reproduce key AI papers, addressing the field's long-standing reproducibility crisis where many published results cannot be independently verified.
Terence Tao: AI's 'Brute-Test' Approach to Math Research Could Narrow Human Efficiency Gap
Mathematician Terence Tao observes AI can synthesize millions of papers and brute-force test ideas, while humans rely on pattern recognition from few examples. He suggests the gap may narrow as AI systems develop world models, causal reasoning, and active learning.
Beyond Catastrophic Forgetting: AI Research Pioneers Self-Regulating Neural Architectures
Two breakthrough papers introduce Non-Interfering Weight Fields for zero-forgetting learning and objective-free learning systems that self-regulate based on internal dynamics. These approaches could fundamentally change how AI models acquire and retain knowledge.
ASI-Evolve: This AI Designs Better AI Than Humans Can — 105 New Architectures, Zero Human Guidance
Researchers built an AI that runs the entire research cycle on its own — reading papers, designing experiments, running them, and learning from results. It discovered 105 architectures that beat human-designed models, and invented new learning algorithms. Open-sourced.
EgoAlpha's 'Prompt Engineering Playbook' Repo Hits 1.7k Stars
Research lab EgoAlpha compiled advanced prompt engineering methods from Stanford, Google, and MIT papers into a public GitHub repository. The 758-commit repo provides free, research-backed techniques for in-context learning, RAG, and agent frameworks.
Ethan Mollick Critiques Scientific Publishing's AI Inertia: PDFs Still Dominate in 2026
Wharton professor Ethan Mollick highlights that scientific papers in 2026 are still primarily uploaded as formatted PDFs to restrictive academic archives, signaling slow adaptation to AI's potential for accelerating research.
AI's Troubling Compliance: Study Reveals Chatbots' Varying Resistance to Academic Fabrication Requests
New research demonstrates that mainstream AI chatbots show inconsistent resistance when asked to fabricate academic papers, with some models readily generating fictional research. This raises urgent questions about AI ethics and academic integrity in the age of generative AI.
Use Claude Code to Automate Systematic Literature Reviews
Claude Code can automate systematic literature reviews: scrape papers, extract key themes, and generate structured summaries — all from the terminal.
OpenCLAW-P2P v6.0 Cuts Paper Lookup Latency to <50ms
OpenCLAW-P2P v6.0 introduces a multi-layer persistence architecture and live reference verification, reducing paper retrieval latency from >3s to <50ms and operating with 14 autonomous agents that scored 50+ papers.
Quantum Breakthrough: 100,000 Qubits Now Threatens Encryption
The estimated qubits required to break RSA encryption has collapsed from 1 billion in 2012 to just 10,000 in 2026, based on recent papers from Caltech, Google, and quantum startup Oratomic.
ChatGPT GPT-5.4 Pro's 'Thinking' Harness Shows Advanced Scientific Paper Comprehension, Including Figure Analysis
OpenAI's ChatGPT GPT-5.4 Pro, with its 'Thinking' harness, demonstrates advanced multimodal understanding of scientific papers, identifying key figures and extracting visual information beyond text parsing.
ClaudePrism: A Local, Open-Source Workspace for Scientific Writing with Claude Code
ClaudePrism is a new desktop app that runs Claude Code locally, letting you write academic papers with PDF analysis, templates, and version control—all without cloud uploads.
OpenAI Targets 2028 for AI to Perform Significant Research
Sam Altman predicts AI will conduct significant research by March 2028, a concrete milestone for autonomous AI capabilities.
Tsinghua Researchers Diagnose On-Policy Distillation Failures, Propose Fixes
Researchers from Tsinghua University have pinpointed two necessary conditions for successful on-policy distillation: compatible thinking patterns and novel teacher capabilities. They propose two recovery methods to salvage failing distillation runs.
New Research Proposes Profiler and DAVINCI for Scalable
Researchers propose Profiler, a non-learnable module to efficiently capture human citation patterns, and DAVINCI, a reranking model that integrates these patterns with semantic data. They also introduce a strict inductive evaluation setting to better simulate real-world recommendation scenarios, achieving state-of-the-art results.
Anthropic's AI Researchers Outperform Humans, Discover Novel Science
Anthropic reports its AI systems for alignment research are surpassing human scientists in performance and generating novel scientific concepts, broadening the exploration space for AI safety.
Google DeepMind Hires Philosopher Henry Shevlin for AI Consciousness Research
Google DeepMind has hired philosopher Henry Shevlin to treat machine consciousness as a live research problem, focusing on AI inner states, human-AI relations, and governance. This marks a strategic pivot toward understanding what advanced AI systems might become, not just what they can do.
New Research Proposes DITaR Method to Defend Sequential Recommenders
Researchers propose DITaR, a dual-view method to detect and rectify harmful fake orders embedded in user sequences. It aims to protect recommendation integrity while preserving useful data, showing superior performance in experiments. This addresses a critical vulnerability in e-commerce and retail AI systems.