1 citations · 1 across the 5 of their papers we have counts for
6 papers
HiSTEVE 1.0: Harnessing Human-Interface VLA Agents for Open-World Games
Zecong Tang, Zian Guan, Yuncheng Guo +3
Building virtual embodied agents that operate in open-ended games like human players is a long-standing goal requiring both long-horizon autonomy and reliable native-interface cont…
SafeRelBench: A Spatial-Relation-Aware Benchmark for Process-Level Safety in VLM-Driven Embodied Agents
Huaigang Yang, Ya Li, Min Ren +3
Vision-language models (VLMs) are increasingly used as the reasoning backbone of embodied agents, enabling robots to interpret visual scenes, follow language instructions, and plan…
NormAct: Benchmarking Embodied Agents' Proactive Compliance with Unspoken Social Norms
Shiyun Zhao, Xinwei Song, Tianyu Guo +7
Embodied agents driven by multimodal large language models (MLLMs) can often complete everyday tasks from visual observations, but goal achievement does not establish whether they…
TongSIM: A General Platform for Simulating Intelligent Machines
Zhe Sun, Kunlun Wu, Chuanjian Fu +24
As artificial intelligence (AI) rapidly advances, especially in multimodal large language models (MLLMs), research focus is shifting from single-modality text processing to the mor…
Reasoning with Exploration: An Entropy Perspective
Daixuan Cheng, Shaohan Huang, Xuekai Zhu +4
Balancing exploration and exploitation is a central goal in reinforcement learning (RL). Despite recent advances in enhancing large language model (LLM) reasoning, most methods lea…
On Domain-Adaptive Post-Training for Multimodal Large Language Models
Daixuan Cheng, Shaohan Huang, Ziyu Zhu +5
Adapting general multimodal large language models (MLLMs) to specific domains, such as scientific and industrial fields, is highly significant in promoting their practical applicat…