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Jemin Lee

4 accepted papers

2025

Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant

IJCAI 2025

Quantization has gained attention as a promising solution for the cost-effective deployment of large and small language models. However, most prior work has been limited to perplexity or basic knowledge tasks and lacks a comprehensive evaluation of recent models like Llama-3.3. In this paper, we con

2024

Visual Preference Inference: An Image Sequence-Based Preference Reasoning in Tabletop Object Manipulation

IROS 2024poster

In robotic object manipulation, human preferences can often be influenced by the visual attributes of objects, such as color and shape. These properties play a crucial role in operating a robot to interact with objects and align with human intention. In this paper, we focus on the problem of inferri…

Cited by 0SourcecodeScholar
2022

CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution

ECCV 2022poster

"Mobile devices run deep learning models for various purposes, such as image classification and speech recognition. Due to the resource constraints of mobile devices, researchers have focused on either making a lightweight deep neural network (DNN) model using model pruning or generating an efficien…