10 papers
Black-Box Detection of LLM-Generated Text Using Generalized Jensen-Shannon Divergence
Shuangyi Chen, Ashish Khisti
We study black-box detection of machine-generated text under practical constraints: the scoring model (proxy LM) may mismatch the unknown source model, and per-input contrastive ge…
Multi-Bitwidth Quantization for LLMs Using Additive Codebooks
Liza Babaoglu, Shuangyi Chen, Ashish Khisti
As large language models (LLMs) are increasingly deployed across heterogeneous hardware with varying resource constraints, the ability to adaptively manage the trade-off between pe…
Multi-Marginal Couplings for Metropolis-Hastings
Buu Phan, Gergely Flamich, Ashish Khisti +1
Convergence diagnosis for Markov chain Monte Carlo is a matter of fundamental importance in computational statistics: it determines the resources allocated to a particular sampling…
Cross-Tokenizer Likelihood Scoring Algorithms for Language Model Distillation
Buu Phan, Ashish Khisti, Karen Ullrich
Computing next-token likelihood ratios between two language models (LMs) is a standard task in training paradigms such as knowledge distillation. Since this requires both models to…
One-Shot Broadcast Joint Source-Channel Coding with Codebook Diversity
Joseph Rowan, Buu Phan, Ashish Khisti
We study a one-shot joint source-channel coding setting where the source is encoded once and broadcast to decoders through independent channels. Success is predicated on at lea…
List-Level Distribution Coupling with Applications to Speculative Decoding and Lossy Compression
Joseph Rowan, Buu Phan, Ashish Khisti
We study a relaxation of the problem of coupling probability distributions -- a list of samples is generated from one distribution and an accept is declared if any one of these sam…