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20232026
most citedSimul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

FuncCode: Compressing Kolmogorov--Arnold Networks in Function Space with Hardware-Aware Quantization

Kazi Ahmed Asif Fuad, Lizhong Chen

Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions, increasing flexibility but also parameter memory because each edge stores multip…

cs.LG2026

BiKAN: Restoring Collapsed Basis of Binary Kolmogorov--Arnold Networks

Kazi Ahmed Asif Fuad, Lizhong Chen

Binarizing a polynomial Kolmogorov--Arnold Network (KAN) not only changes parameter precision, but also alters the function space available to each layer. When activations are rest…

cs.LG2026

SparseKAN: Compressing Kolmogorov--Arnold Networks Across Basis Functions, Neurons, and Bits

Kazi Ahmed Asif Fuad, Lizhong Chen

Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions parameterized by multiple basis coefficients. This introduces a source of redunda…

cs.LG2025

QuantKAN: A Unified Quantization Framework for Kolmogorov Arnold Networks

Kazi Ahmed Asif Fuad, Lizhong Chen

Kolmogorov--Arnold Networks (KANs) replace linear weights with spline-based functions, offering strong expressivity but posing challenges for low-precision deployment due to hetero…

cs.CL2024

LLM-Ref: Enhancing Reference Handling in Technical Writing with Large Language Models

Kazi Ahmed Asif Fuad, Lizhong Chen

Large Language Models (LLMs) excel in data synthesis but can be inaccurate in domain-specific tasks, which retrieval-augmented generation (RAG) systems address by leveraging user-p…

cs.CL2023★ 2 cited

Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models

Victor Agostinelli, Max Wild, Matthew Raffel +2

Large language models (LLMs) with billions of parameters and pretrained on massive amounts of data are now capable of near or better than state-of-the-art performance in a variety…