10 papers
Modeling Hierarchical Thinking in Large Reasoning Models
G M Shahariar, Erfan Shayegani, Ali Nazari +1
Large Reasoning Models (LRMs) solve complex tasks by generating long Chain-of-Thought (CoT) sequences; however, the emergent dynamics governing reasoning trajectories are not well…
VLMs Need Words: Vision Language Models Ignore Visual Detail In Favor of Semantic Anchors
Haz Sameen Shahgir, Xiaofu Chen, Yu Fu +4
Vision-language models (VLMs) have achieved impressive performance across a wide range of multimodal tasks. However, they often fail on tasks that require fine-grained visual perce…
From Measurement to Expertise: Empathetic Expert Adapters for Context-Based Empathy in Conversational AI Agents
Erfan Shayegani, Jina Suh, Andy Wilson +2
Empathy is a critical factor in fostering positive user experiences in conversational AI. While models can display empathy, it is often generic rather than tailored to specific tas…
Cross-Modal Safety Alignment: Is textual unlearning all you need?
Trishna Chakraborty, Erfan Shayegani, Zikui Cai +5
Recent studies reveal that integrating new modalities into Large Language Models (LLMs), such as Vision-Language Models (VLMs), creates a new attack surface that bypasses existing…
Just Do It!? Computer-Use Agents Exhibit Blind Goal-Directedness
Erfan Shayegani, Keegan Hines, Yue Dong +6
Computer-Use Agents (CUAs) are an increasingly deployed class of agents that take actions on GUIs to accomplish user goals. In this paper, we show that CUAs consistently exhibit Bl…
Evil Vizier: Vulnerabilities of LLM-Integrated XR Systems
Yicheng Zhang, Zijian Huang, Sophie Chen +3
Extended reality (XR) applications increasingly integrate Large Language Models (LLMs) to enhance user experience, scene understanding, and even generate executable XR content, and…