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20242026
most citedOn the Fundamental Limits of LLMs at Scale

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cs.LG2025★ 1 cited

On the Fundamental Limits of LLMs at Scale

Muhammad Ahmed Mohsin, Muhammad Umer, Ahsan Bilal +13

Large Language Models (LLMs) have benefited enormously from scaling, yet these gains are bounded by five fundamental limitations: (1) hallucination, (2) context compression, (3) re…

eess.SP2025

minPIC: Towards Optimal Power Allocation in Multi-User Interference Channels

Sagnik Bhattacharya, Abhiram Rao Gorle, John M. Cioffi

6G envisions massive cell-free networks with spatially nested multiple access (MAC) and broadcast (BC) channels without centralized coordination. This makes optimal resource alloca…

cs.NI2025

AI Enabled 6G for Semantic Metaverse: Prospects, Challenges and Solutions for Future Wireless VR

Muhammad Ahmed Mohsin, Sagnik Bhattacharya, Abhiram Gorle +2

Wireless support of virtual reality (VR) has challenges when a network has multiple users, particularly for 3D VR gaming, digital AI avatars, and remote team collaboration. This wo…

cs.IT2025

Information-computation trade-offs in non-linear transforms

Connor Ding, Abhiram Rao Gorle, Jiwon Jeong +2

In this work, we explore the interplay between information and computation in non-linear transform-based compression for broad classes of modern information-processing tasks. We fi…

cs.LG2025

ItDPDM: Information-Theoretic Discrete Poisson Diffusion Model

Sagnik Bhattacharya, Abhiram Gorle, Ahsan Bilal +3

Generative modeling of non-negative, discrete data, such as symbolic music, remains challenging due to two persistent limitations in existing methods. Firstly, many approaches rely…

cs.SD2025

LZMidi: Compression-Based Symbolic Music Generation

Connor Ding, Abhiram Gorle, Sagnik Bhattacharya +3

Recent advances in symbolic music generation primarily rely on deep learning models such as Transformers, GANs, and diffusion models. While these approaches achieve high-quality re…

cs.IT2025

An Information-Theoretic Efficient Capacity Region for Multi-User Interference Channel

Sagnik Bhattacharya, Abhiram Rao Gorle, Muhammad Ali Mohsin +1

We investigate the capacity region of multi-user interference channels (IC), where each user encodes multiple sub-user components. By unifying chain-rule decomposition with the Ent…