2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Channel Simulation and Distributed Compression with Ensemble Rejection Sampling
Buu Phan, Ashish Khisti
We study channel simulation and distributed matching, two fundamental problems with several applications to machine learning, using a recently introduced generalization of the stan…
Delayed Attention Training Improves Length Generalization in Transformer--RNN Hybrids
Buu Phan, Reza Ebrahimi, Sanjay Haresh +1
We study length generalization in sequence models on a composite problem involving both state tracking and associative recall. Prior work finds that recurrent networks handle state…
On Self-Adaptive Perception Loss Function for Sequential Lossy Compression
Sadaf Salehkalaibar, Buu Phan, Likun Cai +4
We consider causal, low-latency, sequential lossy compression, with mean squared-error (MSE) as the distortion loss, and a perception loss function (PLF) to enhance the realism of…