160 citations · 1.5k across the 122 of their papers we have counts for
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Robust Detection of LLM-Generated Text under Contamination
Jiaxun Li, Saptarshi Chakraborty, Ambuj Tewari
We study the detection of LLM-generated text under editing and contamination. Modeling human and machine text as finite-order Markov processes with Huber contamination, we characte…
Is Zero-Shot Super-Resolution Possible in Operator Learning?
Unique Subedi, Ambuj Tewari
Neural operators are often reported to exhibit zero-shot super-resolution, a phenomenon in which a model trained on coarse grids produces accurate predictions on finer testing grid…
Online Conformal Prediction: Enforcing monotonicity via Online Optimization
Eduardo Ochoa Rivera, Ambuj Tewari
Conformal prediction provides a principled framework for uncertainty quantification with finite-sample coverage guarantees. While recent work has extended conformal prediction to o…
Generator-Mediated Bandits: Thompson Sampling for GenAI-Powered Adaptive Interventions
Marc Brooks, Gabriel Durham, Kihyuk Hong +1
Recent advances in generative artificial intelligence (GenAI) models have enabled the generation of personalized content that adapts to up-to-date user context. While personalized…
On Next-Token Prediction in LLMs: How End Goals Determine the Consistency of Decoding Algorithms
Jacob Trauger, Ambuj Tewari
Probabilistic next-token prediction trained using cross-entropy loss is the basis of most large language models. Given a sequence of previous values, next-token prediction assigns…
Operator Learning: A Statistical Perspective
Unique Subedi, Ambuj Tewari
Operator learning has emerged as a powerful tool in scientific computing for approximating mappings between infinite-dimensional function spaces. A primary application of operator…