Category: Large Language Models

• WWW'26 | A New Paradigm for Cross-Task Adaptive Multi-Agent Collaboration
• Math Major, in Crisis! Fields Medalist Tests ChatGPT 5.5 Pro, Achieves Thesis-Level Result in 17 Minutes
• Zero Index, Zero Embedding, Pure Grep: DCI Does Deep Research Directly on Raw Corpora
• Attention Is All You Need Author Returns: Can a 99% Sparse Transformer Be Even Faster?
• The Ghost of Markov: From Predicting the Next Word to Predicting the Next Action
• Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies in LLM Reinforcement Learning
• Compression Is All You Need — A Letter on Mathematics and AI from Fields Medalist Michael Freedman
• Token-Level, Precision Length Control: 3B Model Beats GPT 5.4 and Claude
• Perhaps the Most Impressive AI Paper of Recent Years: After Giving AI Reasoning Real-Time Subtitles, Its Inner Thoughts Are Shocking!
• Hardcore: Google's Jeff Dean Says the Bottleneck for Million-Chip LLM Pre-training Has Been Completely Broken!
• Static Benchmarks ‘Outdated’? OpenKG Continues to Update the LLM Knowledge-Enhanced Dynamic Evaluation Leaderboard Dynamic OneEval-202605
• Leaderboard-Hacking AIs Wiped Out! Meta-Stanford's Hellish Test Leaves GPT/Claude/Gemini Scoring Zero
• Karpathy and Claude Code Creator Boris Drop Latest Interview That's Shaking the Programmer World
• Abstract-CoT: Reasoning Tokens Slashed 11.6x, Chain-of-Thought Without Words Shatters LLM Efficiency Ceiling
• Your Agent Isn't Really Learning—It's Just Flipping Through a Notebook
• The Era of Software 3.0 Has Arrived
• Qwen-Scope: Seeing Through the 'Hidden Thoughts' of Large Models
• The Father of GPT Throws AI Back to 1930: Never Saw a Line of Code, Yet 'Invented' Python!
• Scaling Pain: Lessons from Serving Ultra-Large-Scale Coding Agents
• Skills-Driven Reasoning Paradigm: Tsinghua & Peking University Propose TRS, Saving 59% Tokens Without Accuracy Drop
• Thinking Without Words: Efficient Latent Reasoning with Abstract Chain-of-Thought
• Costs Cut by 90%, Accuracy Hits 100%! MIT's Counterintuitive Architecture Challenges Silicon Valley Dogma
• Can LLMs Enhance Their Own Reasoning? SePT Offers a Simple Online Self-Training Paradigm
• The First Spatio-Temporal Reasoning Framework: Enabling Large Models to Truly Understand Spatio-Temporal Data | ACL'26
• QuantCode-Bench: A Benchmark for Evaluating LLM-Generated Quant Code Quality