22 citations · 102 across the 45 of their papers we have counts for
53 papers
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…
Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction
Mahdi Farahbakhsh, Vishnu Teja Kunde, Dileep Kalathil +2
Diffusion models have been used as priors for solving inverse problems. However, existing approaches typically overlook side information that could significantly improve reconstruc…
Approximate Message Passing for Multi-Preamble Detection in OTFS Random Access
Alessandro Mirri, Vishnu Teja Kunde, Enrico Paolini +1
This article addresses the problem of multiple preamble detection in random access systems based on orthogonal time frequency space (OTFS) signaling. This challenge is formulated a…
Teaching at Scale: Leveraging AI to Evaluate and Elevate Engineering Education
Jean-Francois Chamberland, Martin C. Carlisle, Arul Jayaraman +3
Evaluating teaching effectiveness at scale remains a persistent challenge for large universities, particularly within engineering programs that enroll tens of thousands of students…
Density Evolution Analysis of Sparse-Block IDMA
Jean-Francois Chamberland, Gianluigi Liva, Krishna Narayanan
Sparse block interleaver division multiple access (SB-IDMA) is a recently introduced unsourced multiple access protocol that aims to improve the performance of the grant-free two-s…
Camera-Based Localization and Enhanced Normalized Mutual Information
Vishnu Teja Kunde, Jean-Francois Chamberland, Siddharth Agarwal
Robust and fine localization algorithms are crucial for autonomous driving. For the production of such vehicles as a commodity, affordable sensing solutions and reliable localizati…
Multi-User SR-LDPC Codes
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
This article introduces a novel non-orthogonal multiple access (NOMA) scheme for coordinated uplink channels. The scheme builds on the recently proposed sparse-regression low-densi…
Coding for the unsourced B-channel with erasures: enhancing the linked loop code
William W. Zheng, Jamison R. Ebert, Stefano Rini +1
In [1], the linked loop code (LLC) is presented as a promising code for the unsourced A-channel with erasures (UACE). The UACE is an unsourced multiple access channel in which acti…
Evolution of the 5G New Radio Two-Step Random Access towards 6G Unsourced MAC
Patrick Agostini, Jean-Francois Chamberland, Federico Clazzer +7
This report summarizes some considerations on possible evolutions of grant-free random access in the next generation of the 3GPP wireless cellular standard. The analysis is carried…
Multi-User SR-LDPC Codes via Coded Demixing with Applications to Cell-Free Systems
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
Novel sparse regression LDPC (SR-LDPC) codes exhibit excellent performance over additive white Gaussian noise (AWGN) channels in part due to their natural provision of shaping gain…
Coding for the unsourced A-channel with erasures: the linked loop code
William W. Zheng, Jamison R. Ebert, Stefano Rini +1
The A-channel is a noiseless multiple access channel in which users simultaneously transmit Q-ary symbols and the receiver observes the set of transmitted symbols, but not their mu…
Sparse Regression LDPC Codes
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
This article introduces a novel concatenated coding scheme called sparse regression LDPC (SR-LDPC) codes. An SR-LDPC code consists of an outer non-binary LDPC code and an inner spa…
Transformers are Provably Optimal In-context Estimators for Wireless Communications
Vishnu Teja Kunde, Vicram Rajagopalan, Chandra Shekhara Kaushik Valmeekam +4
Pre-trained transformers exhibit the capability of adapting to new tasks through in-context learning (ICL), where they efficiently utilize a limited set of prompts without explicit…
LLMZip: Lossless Text Compression using Large Language Models
Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan, Dileep Kalathil +2
We provide new estimates of an asymptotic upper bound on the entropy of English using the large language model LLaMA-7B as a predictor for the next token given a window of past tok…
Scalable Cell-Free Massive MIMO Unsourced Random Access System
Michail Gkagkos, Jean-Francois Chamberland, Costas N. Georghiades +1
Cell-Free Massive MIMO systems aim to expand the coverage area of wireless networks by replacing a single high-performance Access Point (AP) with multiple small, distributed APs co…
PolarAir: A Compressed Sensing Scheme for Over-the-Air Federated Learning
Michail Gkagkos, Krishna R. Narayanan, Jean-Francois Chamberland +1
We explore a scheme that enables the training of a deep neural network in a Federated Learning configuration over an additive white Gaussian noise channel. The goal is to create a…
On Sparse Regression LDPC Codes
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
Belief propagation applied to iterative decoding and sparse recovery through approximate message passing (AMP) are two research areas that have seen monumental progress in recent d…
HashBeam: Enabling Feedback Through Downlink Beamforming in Unsourced Random Access
Jamison R. Ebert, Krishna R. Narayanan, Jean-Francois Chamberland
Unsourced random access (URA) has emerged as a candidate paradigm for massive machine-type communication (MTC) in next-generation wireless networks. While many excellent uplink sch…
FASURA: A Scheme for Quasi-Static Massive MIMO Unsourced Random Access Channels
Michail Gkagkos, Krishna R. Narayanan, Jean-Francois Chamberland +1
This article considers the massive MIMO unsourced random access problem on a quasi-static Rayleigh fading channel. Given a fixed message length and a prescribed number of channel u…