An in-depth analysis of ChatGPT’s global adoption and user behavior patterns through OpenAI’s latest research, exploring economic implications for knowledge-...
An in-depth academic exploration of PrunaAI’s curated repository on AI efficiency, examining the theoretical foundations and practical implications of eight ...
An in-depth scholarly examination of five cutting-edge preference optimization techniques including Pref-GRPO, PVPO, DCPO, ARPO, and GRPO-RoC, exploring thei...
An in-depth analysis of Jet-Nemotron’s hybrid architecture and PostNAS methodology, demonstrating breakthrough achievements in balancing model accuracy with ...
An in-depth analysis of how large language models can fall into overthinking patterns during reasoning tasks, and how identifying Reasoning Completion Points...
A comprehensive analysis of aiXiv, the groundbreaking platform that integrates multi-agent workflows and structured peer review systems to accelerate AI-gene...
Exploring the emerging threat of Advertisement Embedding Attacks (AEA) against LLMs, which stealthily inject malicious content into model outputs while maint...
In-depth analysis of 10 key research papers in reinforcement learning post-training since April 2025, providing practical insights for real-world applications
Google and Penn State University jointly developed the Chain-of-Agents framework, presenting an innovative approach to solving long-context processing proble...
Chinese research team developed ARPO, a novel reinforcement learning algorithm that dramatically improves multi-turn LLM agent performance by leveraging entr...
Comprehensive analysis of MoonshotAI’s Kimi K2 technical report examining MuonClip optimizer, large-scale synthetic data pipeline, and core innovations in ne...
Comprehensive analysis of OmniGen2, the open-source unified multimodal model that surpasses GPT-4o with revolutionary in-context generation and instruction-g...
In-depth analysis of Moonshot AI’s Kimi-Researcher, which achieved 26.9% HLE performance through innovative End-to-End agentic reinforcement learning approac...
Stanford researchers conducted a large-scale study with 1,500 workers and 52 AI experts to analyze labor market changes and human-AI collaboration realities ...
Chinese Academy of Sciences research team published in Nature Machine Intelligence that multimodal large language models can spontaneously form object concep...
Nobel Prize winner and Google DeepMind CEO Demis Hassabis reveals stunning vision for AGI achievement timeline and humanity’s future in WIRED interview
A comprehensive analysis of Manus AI’s unique agent loop mechanism and modular architecture that enables complex task execution beyond simple question-answer...