Learning to Better Search with Language Models via Guided Reinforced Self-Training
Seungyong Moon, Bumsoo Park, Hyun Oh Song
Delving into Large Language Models for Effective Time-Series Anomaly Detection
Junwoo Park, Kyudan Jung, Dohyun Lee, Hyuck Lee , Daehoon Gwak , ChaeHun Park, Jaegul Choo, Jaewoong Cho
GOATex: Geometry and Occlusion-Aware Texturing
Hyunjin Kim, Kunho Kim, Adam Lee, Wonkwang Lee
FlashAdventure: A Benchmark for GUI Agents Solving Full Story Arcs in Diverse Adventure Games
Jaewoo Ahn, Junseo Kim, Heeseung Yun, Jaehyeon Son, Dongmin Park, Jaewoong Cho, Gunhee Kim
KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts
Taebaek Hwang, Minseo Kim, Gisang Lee, Seonuk Kim, Hyunjun Eun
Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
Jiwoong Park*, Chaeun Lee*, Yongseok Choi, Sein Park, Deokki Hong, Jungwook Choi
Channel Normalization for Time Series Channel Identification
Seunghan Lee, Taeyoung Park, Kibok Lee
SuFP: Piecewise Bit Allocation Floating-Point for Robust Neural Network Quantization
Geonwoo Ko, Sungyeob Yoo, Seri Ham, Seeyeon Kim, Minkyu Kim, Joo-Young Kim
KRAFTON AI Hits 100! Mini Interview Series🎉
KRAFTON AI Hits 100! Mini Interview Series🎉 KRAFTON AI has officially surpassed 100 members this year! (Cue applause and cheers 🎉) To celebrate this exciting milestone, we sat down for a short interview with the leaders who are driving KRAFTON AI forward 🥰 We’ll be hearing from Kangwook Lee, who oversees the entire …
Finding an LLM That’s Truly Good at Gaming! The Birth of the ‘Orak’ Benchmark
Finding an LLM That’s Truly Good at Gaming! The Birth of the ‘Orak’ Benchmark As technology evolves, the way games are developed and played continues to change. These days, language models (LLMs) are not only conversation partners within games but also help players with gameplay. But have you ever wondered: “Is this LLM actually good …
Finding an LLM That’s Truly Good at Gaming! The Birth of the ‘Orak’ Benchmark Read More »