activity
20142026
most citedFederated Optimization in Heterogeneous Networks

436 citations · 2.1k across the 92 of their papers we have counts for

collaborators

97 papers

cs.LG2026

Federation over Text: Insight Sharing for Multi-Agent Reasoning

Dixi Yao, Tahseen Rabbani, Manzil Zaheer +1

Modern agents specialize in varying domains while there is no clear approach combining different domain skills. We propose a federated learning-like framework, Federation over Text…

cs.LG2026

Differentially Private Model Merging

Qichuan Yin, Manzil Zaheer, Tian Li

In machine learning, privacy requirements at inference or deployment time often evolve due to changing policies, regulations, or user preferences. In this work, we aim to construct…

cs.SE2026

Scaling Test-Time Compute for Agentic Coding

Joongwon Kim, Wannan Yang, Kelvin Niu +13

Test-time scaling has become a powerful way to improve large language models. However, existing methods are best suited to short, bounded outputs that can be directly compared, ran…

cs.LG2026

Interleaved Head Attention

Sai Surya Duvvuri, Chanakya Ekbote, Rachit Bansal +6

Multi-Head Attention (MHA) is the core computational primitive underlying modern Large Language Models (LLMs). However, MHA suffers from a fundamental linear scaling limitation: $H…

cs.LG2026

Asynchronous Heavy-Tailed Optimization

Junfei Sun, Dixi Yao, Xuchen Gong +3

Heavy-tailed stochastic gradient noise, commonly observed in transformer models, can destabilize the optimization process. Recent works mainly focus on developing and understanding…

cs.CR2025

CIMemories: A Compositional Benchmark for Contextual Integrity of Persistent Memory in LLMs

Niloofar Mireshghallah, Neal Mangaokar, Narine Kokhlikyan +4

Large Language Models (LLMs) increasingly use persistent memory from past interactions to enhance personalization and task performance. However, this memory introduces critical ris…