collaborators

5 papers

stat.ML2026

Acceleration of Diffusion Language Model through Discrete Average Generator

Yidong Ouyang, Zhengyan Wan, Themis Haris +8

Discrete diffusion models and flow matching have emerged as powerful frameworks for generative modeling over discrete state spaces, yet efficient few-step generation remains a fund…

cs.LG2026

Elastic Threshold Attention: Learned Contextual Sparsity for Long-Context Decoding

Themistoklis Haris, Henry Li, Maryam Karimzadehgan

Massive KV caches can cause severe memory-bandwidth bottlenecks during long-context decoding. Sparse attention methods mitigate this problem, but often drop necessary context, lead…

cs.IR2026

A Unified Model and Document Representation for On-Device Retrieval-Augmented Generation

Julian Killingback, Ofer Meshi, Henry Li +2

Traditional Retrieval-Augmented Generation (RAG) approaches generally assume that retrieval and generation occur on powerful servers removed from the end user. While this reduces l…

cs.IR2023

Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval

Haolun Wu, Ofer Meshi, Masrour Zoghi +4

Accurate modeling of the diverse and dynamic interests of users remains a significant challenge in the design of personalized recommender systems. Existing user modeling methods, l…

cs.LG2023

Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation

Li Ding, Masrour Zoghi, Guy Tennenholtz +1

We introduce EV3, a novel meta-optimization framework designed to efficiently train scalable machine learning models through an intuitive explore-assess-adapt protocol. In each ite…