3 citations · 3 across the 6 of their papers we have counts for
7 papers
X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation
Ruibin Ju, Ruifeng Cai, Min Xu +1
Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chunk before replanning amortizes…
Resilience Matters for Embodied Agents System: New Metrics, Systematic Evaluation, and Optimization
Yapeng Liu, Yuanzhao Zhai, Xudong Gong +4
Embodied Agents System (EAS) are increasingly deployed in open-world physical domains, where reliability directly dictates deployment quality and human-agent trust. However, existi…
Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning
Yapeng Liu, Yuanzhao Zhai, Bo Ding +2
Physically consistent motion planning remains a fundamental challenge in embodied AI, as generated trajectories must strictly conform to real-world execution dynamics. While latent…
AutoPrompt: Automated Red-Teaming of Text-to-Image Models via LLM-Driven Adversarial Prompts
Yufan Liu, Wanqian Zhang, Huashan Chen +4
Despite rapid advancements in text-to-image (T2I) models, their safety mechanisms are vulnerable to adversarial prompts, which maliciously generate unsafe images. Current red-teami…
PhysPatch: A Physically Realizable and Transferable Adversarial Patch Attack for Multimodal Large Language Models-based Autonomous Driving Systems
Qi Guo, Xiaojun Jia, Shanmin Pang +5
Multimodal Large Language Models (MLLMs) are becoming integral to autonomous driving (AD) systems due to their strong vision-language reasoning capabilities. However, MLLMs are vul…
MetaRuleGPT: Recursive Numerical Reasoning of Language Models Trained with Simple Rules
Kejie Chen, Lin Wang, Qinghai Zhang +1
Recent studies have highlighted the limitations of large language models in mathematical reasoning, particularly their inability to capture the underlying logic. Inspired by meta-l…
YAYI 2: Multilingual Open-Source Large Language Models
Yin Luo, Qingchao Kong, Nan Xu +50
As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world…