activity
20232026
most citedA Survey on Model Compression for Large Language Models

37 citations · 39 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models

Liuyuan Wen, Xun Zhu, Lihao Huang +2

Large Language Models exhibit paradoxical fragility in fundamental arithmetic, implying a disconnect between internal computation and discrete output. By analyzing the residual str…

cs.CL2024

Improving Mathematical Reasoning Capabilities of Small Language Models via Feedback-Driven Distillation

Xunyu Zhu, Jian Li, Can Ma +1

Large Language Models (LLMs) demonstrate exceptional reasoning capabilities, often achieving state-of-the-art performance in various tasks. However, their substantial computational…

cs.CL2024★ 1 cited

Key-Point-Driven Mathematical Reasoning Distillation of Large Language Model

Xunyu Zhu, Jian Li, Can Ma +1

Large Language Models (LLMs) have demonstrated exceptional proficiency in mathematical reasoning tasks due to their extensive parameter counts and training on vast datasets. Despit…

cs.CL2024

Distilling Mathematical Reasoning Capabilities into Small Language Models

Xunyu Zhu, Jian Li, Yong Liu +2

This work addresses the challenge of democratizing advanced Large Language Models (LLMs) by compressing their mathematical reasoning capabilities into sub-billion parameter Small L…

cs.CL2023★ 37 cited

A Survey on Model Compression for Large Language Models

Xunyu Zhu, Jian Li, Yong Liu +2

Large Language Models (LLMs) have transformed natural language processing tasks successfully. Yet, their large size and high computational needs pose challenges for practical use,…

cs.LG2023★ 1 cited

Robust Neural Architecture Search

Xunyu Zhu, Jian Li, Yong Liu +1

Neural Architectures Search (NAS) becomes more and more popular over these years. However, NAS-generated models tends to suffer greater vulnerability to various malicious attacks.…

cs.CV2023

Improving Differentiable Architecture Search via Self-Distillation

Xunyu Zhu, Jian Li, Yong Liu +1

Differentiable Architecture Search (DARTS) is a simple yet efficient Neural Architecture Search (NAS) method. During the search stage, DARTS trains a supernet by jointly optimizing…