2 citations · 6 across the 13 of their papers we have counts for
13 papers
ETA: A New Agentic Paradigm for Embodied Tasks
Yitong Chen, Zezheng Huai, Sixian Li +7
When will robots have their ChatGPT moment? Such a breakthrough requires a general-purpose robot that can handle unfamiliar tasks in unfamiliar environments, remain controllable ov…
Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias
Zixiang Xu, Sixian Li, Huaxing Liu +4
Existing studies of LLM-as-judge scoring bias work predominantly at the input-output level: they perturb inputs, measure score deltas, and propose prompt-level mitigations. We argu…
CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts
Haozhe Zhang, Sixian Li, Yifei Zhang +5
Vision-language-action (VLA) models have advanced generalist robotic manipulation, yet real-world deployment reveals a fundamental challenge: robots are equipped with diverse and h…
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models
Jinhao Wu, Shiduo Zhang, Yicheng Liu +9
Most vision-language-action (VLA) models map observations directly to actions without explicit intermediate planning, which limits performance on long-horizon tasks where early mis…
DFPO: Scaling Value Modeling via Distributional Flow towards Robust and Generalizable LLM Post-Training
Dingwei Zhu, Zhiheng Xi, Shihan Dou +17
Training reinforcement learning (RL) systems in real-world environments remains challenging due to noisy supervision and poor out-of-domain (OOD) generalization, especially in LLM…
FRoM-W1: Towards General Humanoid Whole-Body Control with Language Instructions
Peng Li, Zihan Zhuang, Yangfan Gao +16
Humanoid robots are capable of performing various actions such as greeting, dancing and even backflipping. However, these motions are often hard-coded or specifically trained, whic…
DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training
Dingwei Zhu, Zhiheng Xi, Shihan Dou +15
Reinforcement learning (RL) has shown strong performance in LLM post-training, but real-world deployment often involves noisy or incomplete supervision. In such settings, complex a…
SocialMaze: A Benchmark for Evaluating and Enhancing Social Reasoning in Large Language Models in Complex Social Environments
Zixiang Xu, Yanbo Wang, Yue Huang +13
Large language models (LLMs) are increasingly deployed in socially grounded applications, where success requires interpreting context, inferring others' mental states, and reasonin…
TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use
Junjie Ye, Yilong Wu, Sixian Li +9
Large language models (LLMs) achieve remarkable advancements by leveraging tools to interact with environments, a critical step toward generalized AI. However, the standard supervi…
SafeAligner: Safety Alignment against Jailbreak Attacks via Response Disparity Guidance
Caishuang Huang, Wanxu Zhao, Rui Zheng +11
As the development of large language models (LLMs) rapidly advances, securing these models effectively without compromising their utility has become a pivotal area of research. How…
ToolSword: Unveiling Safety Issues of Large Language Models in Tool Learning Across Three Stages
Junjie Ye, Sixian Li, Guanyu Li +6
Tool learning is widely acknowledged as a foundational approach or deploying large language models (LLMs) in real-world scenarios. While current research primarily emphasizes lever…
RoTBench: A Multi-Level Benchmark for Evaluating the Robustness of Large Language Models in Tool Learning
Junjie Ye, Yilong Wu, Songyang Gao +7
Tool learning has generated widespread interest as a vital means of interaction between Large Language Models (LLMs) and the physical world. Current research predominantly emphasiz…
ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios
Junjie Ye, Guanyu Li, Songyang Gao +9
Existing evaluations of tool learning primarily focus on validating the alignment of selected tools for large language models (LLMs) with expected outcomes. However, these approach…