collaborators

10 papers

cs.CL2026

PI-Mem: Pushing Long-Context Reasoning to 3.6M Tokens with Parallel-Iterative Memory

Dawei Liu, Haixu Song, Shuang Cheng +9

Long-context reasoning remains a critical bottleneck for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates ca…

cs.CV2026

Cosmos 3: Omnimodal World Models for Physical AI

NVIDIA, :, Aditi +293

We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…

cs.AI2026

MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop

Yikun Fu, Bowen Fu, Zhenyu Wu +10

Computer use agents (CUAs) have advanced rapidly in desktop automation, and a growing number of users deploy CUAs such as OpenClaw on Mac Mini for always-on automation. However, ex…

cs.IR2026

Mixture-of-Experts Knowledge Graph Retrieval-Augmented Generation for Multi-Agent LLM-based Recommendation

Shijie Wang, Chengyi Liu, Yujuan Ding +4

Large language models (LLMs) have recently been adopted for recommendations due to their ability to understand user intent and item semantics. However, LLM-based recommender system…

cs.AI2026

UnityMAS-O: A General RL Optimization Framework for LLM-Based Multi-Agent Systems

Yiqun Chen, Wei Yang, Erhan Zhang +14

LLM-based multi-agent systems decompose complex tasks into interacting roles, but most remain manually orchestrated by prompts, tools, and control rules, while agents are rarely op…

cs.AI2026

MARS: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation

Pengfei Li, Shijie Wang, Fangyuan Li +7

Reinforcement learning (RL) paradigms have demonstrated strong performance on reasoning-intensive tasks such as code generation. However, limited trajectory diversity often leads t…