6 papers
Streaming Interventions: Can Video Large Language Models Correct Mistakes as They Occur?
Apratim Bhattacharyya, Shweta Mahajan, Sanjay Haresh +5
Learning everyday skills, like cooking a dish, relies increasingly on instructional media such as online videos. This opens the door to the use of video (and multimodal) large lang…
From Out-of-Distribution Detection to Hallucination Detection: A Geometric View
Litian Liu, Reza Pourreza, Yubing Jian +2
Detecting hallucinations in large language models is a critical open problem with significant implications for safety and reliability. While existing hallucination detection method…
Enhancing Hallucination Detection through Noise Injection
Litian Liu, Reza Pourreza, Sunny Panchal +4
Large Language Models (LLMs) are prone to generating plausible yet incorrect responses, known as hallucinations. Effectively detecting hallucinations is therefore crucial for the s…
What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction
Sunny Panchal, Apratim Bhattacharyya, Guillaume Berger +10
Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, where each turn must be stepped (i.e…
Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?
Apratim Bhattacharyya, Bicheng Xu, Sanjay Haresh +6
Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance, a key capability for future AI a…
Can Vision-Language Models Answer Face to Face Questions in the Real-World?
Reza Pourreza, Rishit Dagli, Apratim Bhattacharyya +3
AI models have made significant strides in recent years in their ability to describe and answer questions about real-world images. They have also made progress in the ability to co…