collaborators

5 papers

cs.AI2026

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…

cs.IT2026

Optimal Multi-bit Generative Watermarking Schemes Under Worst-Case False-Alarm Constraints

Yu-Shin Huang, Chao Tian, Krishna Narayanan

This paper considers the problem of multi-bit generative watermarking for large language models under a worst-case false-alarm constraint. Prior work established a lower bound on t…

cs.LG2026

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…

cs.CV2025

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…

cs.IT2025

In-Context Learning for Gradient-Free Receiver Adaptation: Principles, Applications, and Theory

Matteo Zecchin, Tomer Raviv, Dileep Kalathil +3

In recent years, deep learning has facilitated the creation of wireless receivers capable of functioning effectively in conditions that challenge traditional model-based designs. L…