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Taeho Kim

4 accepted papers

2025

ESPRESSO: An Effective Approach to Passage Retrieval for High-Quality Conversational Recommender Systems

AAAI 2025technical

Conversational Recommender Systems (CRS) aim to provide tailored recommendation responses via a chat interface, including both the user's preferred item and its accompanying explanation. However, due to its generative nature, CRS are prone to responding with factually incorrect explanations (i.e., h…

2024

LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

IJCAI 2024poster

Fine-tuning pre-trained large language models (LLMs) with limited hardware presents challenges due to GPU memory constraints. Various distributed fine-tuning methods have been proposed to alleviate memory constraints on GPU. However, determining the most effective method for achieving rapid fine-tun…

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…