3 papers
cs.DC2026
ARL-Tangram: Unleash the Resource Efficiency in Agentic Reinforcement Learning
Bangjun Xiao, Yihao Zhao, Xiangwei Deng +9
Agentic reinforcement learning (RL) has emerged as a transformative workload in cloud clusters, enabling large language models (LLMs) to solve complex problems through interactions…
cs.CL2026
TeleMem: Building Long-Term and Multimodal Memory for Agentic AI
Chunliang Chen, Ming Guan, Xiao Lin +8
Large language models (LLMs) excel at many NLP tasks but struggle to sustain long-term interactions due to limited attention over extended dialogue histories. Retrieval-augmented g…
cs.CL2025
MiMo-Audio: Audio Language Models are Few-Shot Learners
Core Team, Dong Zhang, Gang Wang +97
Existing audio language models typically rely on task-specific fine-tuning to accomplish particular audio tasks. In contrast, humans are able to generalize to new audio tasks with…