5 papers
CoMaTrack: Competitive Multi-Agent Game-Theoretic Tracking with Vision-Language-Action Models
Youzhi Liu, Li Gao, Liu Liu +2
Embodied Visual Tracking (EVT), a core dynamic task in embodied intelligence, requires an agent to precisely follow a language-specified target. Yet most existing methods rely on s…
Light Alignment Improves LLM Safety via Model Self-Reflection with a Single Neuron
Sicheng Shen, Mingyang Lv, Han Shen +7
The safety of large language models (LLMs) has increasingly emerged as a fundamental aspect of their development. Existing safety alignment for LLMs is predominantly achieved throu…
TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers
Sicheng Shen, Mingyang Lv, Bing Han +4
In recent years, Spiking Neural Networks (SNNs) have achieved remarkable progress, with Spiking Transformers emerging as a promising architecture for energy-efficient sequence mode…
SafeMind: Benchmarking and Mitigating Safety Risks in Embodied LLM Agents
Ruolin Chen, Yinqian Sun, Jihang Wang +3
Embodied agents powered by large language models (LLMs) inherit advanced planning capabilities; however, their direct interaction with the physical world exposes them to safety vul…
CAFEs: Cable-driven Collaborative Floating End-Effectors for Agriculture Applications
Hung Hon Cheng, Josie Hughes
CAFEs (Collaborative Agricultural Floating End-effectors) is a new robot design and control approach to automating large-scale agricultural tasks. Based upon a cable driven robot a…