9 citations · 12 across the 12 of their papers we have counts for
7 papers · 1 filter
IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems
A. Jian Yang, An Huang, Bo Dan +173
We present IQuest-Q1, a sparse Mixture-of-Experts (MoE) agentic foundation model with 320B total parameters (15B activated). IQuest-Q1 is developed through a three-stage process: (…
From Digital Human Interactions to Physics-Based Humanoid Skills: Physics-Grounded Post-Training of Interaction Generators
Kerui Chen, Jianrong Zhang, Kai Lv +1
Recent methods have made promising progress in generating interactions between two humanoids, largely relying on physics-based tracking policies to convert digital reference motion…
Group Perspective Matters: Regulating Debate Relationships Can Mitigate Blind Conformity in Multi-Agent Debate
Hao Wu, Shoucheng Song, Chang Yao +4
Multi-Agent Debate (MAD) improves the reasoning performance of Large Language Models (LLMs) through multi-round interaction. However, LLMs in MAD are highly susceptible to blind co…
From Pixels to Temporal Correlations: Learning Informative Representations for Reinforcement Learning Pre-training
Jinwen Wang, Youfang Lin, Xiaobo Hu +4
Unsupervised pre-training on large-scale datasets has demonstrated significant potential for improving the sample efficiency and performance of Reinforcement Learning (RL). Given t…
Local Motion Matters: A Deconstruct-Recompose Paradigm for Reinforcement Learning Pre-training from Videos
Jinwen Wang, Youfang Lin, Xiaobo Hu +2
Pre-training on large-scale videos to improve reinforcement learning efficiency is promising yet remains challenging. Existing methods typically treat the agent as an indivisible e…
Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization
Jinwen Wang, Youfang Lin, Xiaobo Hu +4
Visual Reinforcement Learning (VRL) has achieved considerable success in solving control tasks. However, generalizing learned policies to new environments remains a major challenge…
DRFormer: A Dual-Regularized Bidirectional Transformer for Person Re-identification
Ying Shu, Pujian Zhan, Huiqi Yang +3
Both fine-grained discriminative details and global semantic features can contribute to solving person re-identification challenges, such as occlusion and pose variations. Vision f…