Category: Large Language Models

• How Strong is the Reasoning Ability of Large Language Models? A Study Reveals LLMs' Limitations and Potential
• Breakthrough in Reasoning: How SoftCoT++ Enables LLMs to 'Think Multiple Paths'?
• Qwen Breakthrough: Using "Parallel Computing" Instead of "Stacking Parameters", New Method Reduces Memory by 22x, Latency by 6x
• ZeroSearch: <Alibaba Technology> Large Language Models Learn Through Self-Rewarding Without a Browser
• Jeff Dean: AI Will Replace Junior Engineers Within a Year, Netizens: "Altman Only Pitches, What Jeff Says Is Fatal"
• AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale
• Ant Group's Wu Wei: A Big Guess on the Next Generation 'Reasoning' Model Paradigm
• From Intuition to "Deep Thinking": Multidimensional Evolution of Large Model Reasoning Capabilities
• DeepSeek Accuracy and Efficiency Doubled, Huawei & CAS Propose Chain-of-Thought "Early Exit" Mechanism
• GPT-5 R&D Insider Details Revealed! OpenAI Chief Research Officer: AGI is Just Around the Corner
• ZeroSearch: Zero-Search Reinforcement Incentivizes Model Potential, Ushering in a New Era for LLM Search Capability
• Forcing Models to Argue with Themselves, Recursive Thinking CoT Version Soars in Popularity! Netizens: Isn't This Just the Usual Trick for Most Reasoning Models?
• Stanford's Weak-for-Strong (W4S): Harnessing Stronger LLMs with Meta-Agent, Accuracy Boosted to 95.4% | Latest
• Can a single data point significantly enhance the mathematical reasoning performance of large models?
• Research: LLM's Prefilling Feature Has Become Its Jailbreak Vulnerability!
• PKU, Tsinghua, UvA, CMU, etc. Jointly Release: Latest Survey on Logical Reasoning Abilities of Large Models
• NVIDIA's Llama Nemotron Series: Key Technologies Explained
• Microsoft Research Asia SYNTHLLM: Validating Scaling Laws for Synthetic Data for Language Models
• When ChatGPT Broke an Entire Field: An Oral History
• Why LLM Agents Perform Poorly: Google DeepMind Research Reveals Three Failure Modes, RL Fine-tuning Can Mitigate
• ZTE Wireless Institute "Large Model Diving" Team Releases LLM-Adaptive Question Difficulty Distillation Method, Significantly Enhancing Small Model Reasoning Capabilities
• ZTE Research: LLM Adaptive Question Difficulty Grading Distillation Gives Small Models 'Long Chain Thinking'
• AI's Second Half: From Algorithms to Utility
• Large Language Models Are Definitely Not the End Station to Artificial General Intelligence!
• The 'Olympics' of AI? OpenAI Releases New Benchmark MRCR, Pushing Models' 'Needle in a Haystack' Ability to the Limit!