3 papers
cs.CL2026
PROMPT2BOX: Uncovering Entailment Structure among LLM Prompts
Neeladri Bhuiya, Shib Sankar Dasgupta, Andrew McCallum +1
To discover the weaknesses of LLMs, researchers often embed prompts into a vector space and cluster them to extract insightful patterns. However, vector embeddings primarily captur…
cs.CR2026
PLAGUE: Plug-and-play framework for Lifelong Adaptive Generation of Multi-turn Exploits
Neeladri Bhuiya, Madhav Aggarwal, Diptanshu Purwar
Large Language Models (LLMs) are improving at an exceptional rate. With the advent of agentic workflows, multi-turn dialogue has become the de facto mode of interaction with LLMs f…
cs.CL2024
Seemingly Plausible Distractors in Multi-Hop Reasoning: Are Large Language Models Attentive Readers?
Neeladri Bhuiya, Viktor Schlegel, Stefan Winkler
State-of-the-art Large Language Models (LLMs) are accredited with an increasing number of different capabilities, ranging from reading comprehension, over advanced mathematical and…