2 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment
Janghwan Lee, Seongmin Park, Sukjin Hong +3
The rapid advancement of large language models (LLMs) has facilitated their transformation into conversational chatbots that can grasp contextual nuances and generate pertinent sen…
Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization
Janghwan Lee, Minsoo Kim, Seungcheol Baek +3
Large Language Models (LLMs) are proficient in natural language processing tasks, but their deployment is often restricted by extensive parameter sizes and computational demands. T…
Token-Scaled Logit Distillation for Ternary Weight Generative Language Models
Minsoo Kim, Sihwa Lee, Janghwan Lee +4
Generative Language Models (GLMs) have shown impressive performance in tasks such as text generation, understanding, and reasoning. However, the large model size poses challenges f…