6 papers
LENS: Adaptive Spatio-Temporal Zooming for Keyframe Sampling in Long-Form Videos
Ce Zhang, Jinxi He, Katia Sycara +1
Despite rapid progress in Multi-modal Large Language Models (MLLMs), understanding long-form videos is still bottlenecked by limited context windows. While recent keyframe sampling…
Jailbreaking Frontier Foundation Models Through Intention Deception
Xinhe Wang, Katia Sycara, Yaqi Xie
Large (vision-)language models exhibit remarkable capability but remain highly susceptible to jailbreaking. Existing safety training approaches aim to have the model learn a refusa…
Generalizable Dense Reward for Long-Horizon Robotic Tasks
Silong Yong, Stephen Sheng, Carl Qi +6
Existing robotic foundation policies are trained primarily via large-scale imitation learning. While such models demonstrate strong capabilities, they often struggle with long-hori…
Evolving Contextual Safety in Multi-Modal Large Language Models via Inference-Time Self-Reflective Memory
Ce Zhang, Jinxi He, Junyi He +2
Multi-modal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of visual reasoning tasks, yet their vulnerability to safety risks remains a pres…
pySpatial: Generating 3D Visual Programs for Zero-Shot Spatial Reasoning
Zhanpeng Luo, Ce Zhang, Silong Yong +6
Multi-modal Large Language Models (MLLMs) have demonstrated strong capabilities in general-purpose perception and reasoning, but they still struggle with tasks that require spatial…
Aligning LLM+PDDL Symbolic Plans with Human Objective Specifications through Evolutionary Algorithm Guidance
Owen Burns, Dana Hughes, Katia Sycara
Automated planning using a symbolic planning language, such as PDDL, is a general approach to producing optimal plans to achieve a stated goal. However, creating suitable machine u…