2 citations · 3 across the 7 of their papers we have counts for
7 papers
SeaSlides: Semantic Abstraction Layer for Agentic Slide Generation
Shengjun Fang, Chenyang Wu, Zongzhang Zhang
Agentic presentation generation must preserve source content, maintain coherent visual design, render specialized objects, and produce usable artifacts. Existing systems meet only…
ASTER: Agentic Scaling with Tool-integrated Extended Reasoning
Xuqin Zhang, Quan He, Zhenrui Zheng +3
Reinforcement learning (RL) has emerged as a dominant paradigm for eliciting long-horizon reasoning in Large Language Models (LLMs). However, scaling Tool-Integrated Reasoning (TIR…
Reward Models in Deep Reinforcement Learning: A Survey
Rui Yu, Shenghua Wan, Yucen Wang +4
In reinforcement learning (RL), agents continually interact with the environment and use the feedback to refine their behavior. To guide policy optimization, reward models are intr…
Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space
Zhikai Zhang, Chao Chen, Han Xue +6
Humans possess a large reachable space in the 3D world, enabling interaction with objects at varying heights and distances. However, realizing such large-space reaching on humanoid…
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
Chen-Xiao Gao, Chenyang Wu, Mingjun Cao +3
Behavior regularization, which constrains the policy to stay close to some behavior policy, is widely used in offline reinforcement learning (RL) to manage the risk of hazardous ex…
Reinforced In-Context Black-Box Optimization
Lei Song, Chenxiao Gao, Ke Xue +5
Black-Box Optimization (BBO) has found successful applications in many fields of science and engineering. Recently, there has been a growing interest in meta-learning particular co…