22 citations · 102 across the 45 of their papers we have counts for
6 papers · 1 filter
AgentDiscover: Autonomous Discovery with Minimal Search Scaffolding
Mahdi Farahbakhsh, Ilan Sela, Fatemeh Doudi +4
Frameworks that use large language models for scientific discovery typically rely on a fixed, human-designed algorithm that decides what the model sees at each step, leaving the mo…
Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels
Vishnu Teja Kunde, Jean-Francois Chamberland, Krishna R. Narayanan +1
Learning, prediction, and compression are intimately connected: a model that accurately predicts the next symbol in a sequence can be coupled with a source coder to compress that s…
Complex Approximate Message Passing with Non-separable Denoising
Vishnu Teja Kunde, Alessandro Mirri, Jean-Francois Chamberland +1
Approximate Message Passing (AMP) is a general framework for iterative algorithms, originally developed for compressed sensing and later extended to a wide range of high-dimensiona…
Reed--Muller Codes Achieve the Symmetric Capacity on Finite-State Channels
Henry D. Pfister, Navin Kashyap, Jean-Francois Chamberland +1
We study reliable communication over finite-state channels (FSCs) using Reed--Muller (RM) codes. Building on recent symmetry-based analyses for memoryless channels, we show that a…
Bipartite matching under communication constraints
Moonmoon Mohanty, Gautham Bolar, Preetam Patil +3
In modern data center networks, thousands of hosts contend for shared link capacity; the scale of these systems makes centralized scheduling impractical. This article models such s…
Reinforcement Learning for Diffusion LLMs with Entropy-Guided Step Selection and Stepwise Advantages
Vishnu Teja Kunde, Fatemeh Doudi, Mahdi Farahbakhsh +3
Reinforcement learning (RL) has been effective for post-training autoregressive (AR) language models, but extending these methods to diffusion language models (DLMs) is challenging…