4 papers
Towards a Belief-Based World Model for LLM Agents
Shubham Kumar, Harshit Kumar, Narendra Ahuja +1
Large language models (LLMs) are being used as policies for autonomous decision-making and planning in many domains. Despite their strong reasoning capabilities, LLMs struggle with…
Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models
Shubham Kumar, Narendra Ahuja
Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understanding of why LLMs are suscep…
Can MLLMs Find Their Way in a City? Exploring Emergent Navigation from Web-Scale Knowledge
Dwip Dalal, Utkarsh Mishra, Narendra Ahuja +1
Leveraging multimodal large language models (MLLMs) to develop embodied agents offers significant promise for addressing complex real-world tasks. However, current evaluation bench…
Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition
Xiaodan Hu, Chuhang Zou, Suchen Wang +2
Recent video action recognition methods have shown excellent performance by adapting large-scale pre-trained language-image models to the video domain. However, language models con…