분류 전체보기358 [2025-2] 전연주 - Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning 논문 링크: https://arxiv.org/abs/2407.16920 Train-Attention: Meta-Learning Where to Focus in Continual Knowledge LearningPrevious studies on continual knowledge learning (CKL) in large language models (LLMs) have predominantly focused on approaches such as regularization, architectural modifications, and rehearsal techniques to mitigate catastrophic forgetting. However, thesarxiv.orgConference: Neur.. 2025. 12. 6. [2025-2] 박제우 - The Impact of Reasoning Step Length on Large Language Models https://arxiv.org/abs/2401.04925 The Impact of Reasoning Step Length on Large Language ModelsChain of Thought (CoT) is significant in improving the reasoning abilities of large language models (LLMs). However, the correlation between the effectiveness of CoT and the length of reasoning steps in prompts remains largely unknown. To shed light on thiarxiv.org본 논문은 2024 ACL Findings에 등재된 논문으로, 2025년.. 2025. 12. 6. [2025-2] 주서영 - Paint by Example: Exemplar-based Image Editing with Diffusion Model Paint by Example (CVPR 2023)요약예시 기반 이미지 편집에 관한 논문self-supervised training을 활용하여 원본과 참조 이미를 분리시켜 학습을 구성원본 이미지(source image, $s$): 편집하고자 하는 이미지참조 이미지(reference image, $r$): 데이터베이스에서 검색 or 사용자가 제공하는 이미지arifact를 피하고 단순 복-붙 방지Content bottleneckStrong augmentationsArbitrary shape maskClassifier-free guidance학습은 반복없이 단일 forward로 진행 1. Introduction참조 이미지를 조건으로 하는 Diffusion Model을 훈련하기하지만 학습 데이터 쌍을 수집하기 .. 2025. 12. 5. [2025-2] 백승우 - Toward Autonomous UI Exploration: The UIExplorer Benchmark https://arxiv.org/abs/2506.17779 2025. 12. 3. 이전 1 2 3 4 ··· 90 다음
