11 citations · 23 across the 12 of their papers we have counts for
3 papers · 1 filter
CoDA: A Context-Decoupled Hierarchical Agent with Reinforcement Learning
Xuanzhang Liu, Jianglun Feng, Zhuoran Zhuang +7
Large Language Model (LLM) agents trained with reinforcement learning (RL) show great promise for solving complex, multi-step tasks. However, their performance is often crippled by…
Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought
Tencent Hunyuan Team, Ao Liu, Botong Zhou +248
As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…
OpenAgents: An Open Platform for Language Agents in the Wild
Tianbao Xie, Fan Zhou, Zhoujun Cheng +13
Language agents show potential in being capable of utilizing natural language for varied and intricate tasks in diverse environments, particularly when built upon large language mo…