Can AI truly master the art of dynamic, human-like presentation creation? Researchers from the Chinese Information Processing Lab and the University of Chinese Academy of Sciences unveil DeepPresenter. This innovative AI framework introduces "environment-grounded reflection,"
@jiqizhixin
-
LaPha: AI Agents Think Exponentially Better in Poincaré Space
By
–
How can we give AI agents exponentially more room to think and solve complex problems? Researchers from Shanghai Academy of AI for Science, CMU, and others unveil LaPha. This new method trains AlphaZero-like LLM agents in a unique "Poincaré latent space." It leverages negative
-
EMPA Framework Evaluates LLM Empathy Across Sustained Conversations
By
–
Is your AI truly empathetic to your unique needs, turn after turn? Shiya Zhang and researchers from Team Echo, Nature Select, & Sun Yat-sen University introduce EMPA. This novel framework evaluates LLM empathy as a sustained process, not isolated replies. It simulates
-
Claude Code Virtual Pet Buddy Feature Now Available
By
–
The virtual pet Buddy in Claude Code is now officially available! Hurry up and update, then type /buddy to activate yours.
-
Proxy-GS: Lightweight Mesh Transforms 3D Occlusion Relationships
By
–
CVPR 2026 perfect-score paper! A joint team from Shanghai Jiao Tong University, Shanghai AI Lab, Northwestern Polytechnical University, and Sichuan University presents Proxy-GS! Proxy-GS uses a lightweight "proxy mesh" to transform complex occlusion relationships into clear
-
RISE Framework Enables Robots Self-Improvement Through Imagination
By
–
What if robots could learn complex, real-world tasks significantly faster and safer, all by just imagining? Jiazhi Yang and a team from The Chinese University of Hong Kong, Kinetix AI, and Tsinghua University just unveiled RISE. This framework lets robots self-improve by
-
Claude Code Accidentally Open-Sourced Breaking News
By
–
Breaking!
Claude Code got “open-sourced”… or should I say, accidentally liberated -
Federated Learning System Intelligently Routes Tasks to Optimal Clients
By
–
What if your federated learning system could intelligently guide new tasks to the best client, rather than just aggregating data? Researchers from Renmin University of China, Zhongnan University of Economics and Law, Meta, and East China Normal University present a novel
-
LLM Training Without Massive Human-Labeled Datasets Analysis
By
–
How far can we push LLM training without relying on massive human-labeled datasets? A collaborative effort from Tsinghua University, Shanghai AI Lab, UIUC, and other leading institutions provides crucial insights. They conducted a comprehensive analysis of Unsupervised