3 papers
cs.LG2026
Geometry-Aware Hallucination Detection in Large Language Models
Bodla Krishna Vamshi, Rohan Bhatnagar, Haizhao Yang
Large language models (LLMs) frequently generate factually incorrect or unsupported content, commonly referred to as hallucinations. Prior work has explored decoding strategies, re…
cs.CL2026
DRIFT: Detecting Representational Inconsistencies for Factual Truthfulness
Rohan Bhatnagar, Youran Sun, Chi Andrew Zhang +2
LLMs often produce fluent but incorrect answers, yet detecting such hallucinations typically requires multiple sampling passes or post-hoc verification, adding significant latency…
cs.LG2025
From Equations to Insights: Unraveling Symbolic Structures in PDEs with LLMs
Rohan Bhatnagar, Ling Liang, Krish Patel +1
Motivated by the remarkable success of artificial intelligence (AI) across diverse fields, the application of AI to solve scientific problems, often formulated as partial different…