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pro vyhledávání: '"An, JaeWoo"'
Autor:
An, Honggyu, Kim, Jinhyeon, Park, Seonghoon, Jung, Jaewoo, Han, Jisang, Hong, Sunghwan, Kim, Seungryong
In this work, we explore new perspectives on cross-view completion learning by drawing an analogy to self-supervised correspondence learning. Through our analysis, we demonstrate that the cross-attention map within cross-view completion models captur
Externí odkaz:
http://arxiv.org/abs/2412.09072
Understanding the internal computations of large language models (LLMs) is crucial for aligning them with human values and preventing undesirable behaviors like toxic content generation. However, mechanistic interpretability is hindered by polysemant
Externí odkaz:
http://arxiv.org/abs/2412.04139
Autor:
Kim, Jindae, Song, Jaewoo
Recently, Large Language Model (LLM)-based Fault Localization (FL) techniques have been proposed, and showed improved performance with explanations on FL results. However, a major issue with LLM-based FL techniques is their heavy reliance on LLMs, wh
Externí odkaz:
http://arxiv.org/abs/2412.01005
In this article, we investigate the rank index of projective curves $\mathscr{C} \subset \mathbb{P}^r$ of degree $r+1$ when $\mathscr{C} = \pi_p (\tilde{\mathscr{C}})$ for the standard rational normal curve $\tilde{\mathscr{C}} \subset \mathbb{P}^{r+
Externí odkaz:
http://arxiv.org/abs/2411.17494
In anomaly detection, the scarcity of anomalous data compared to normal data poses a challenge in effectively utilizing deep neural network representations to identify anomalous features. From a data-centric perspective, generative models can solve t
Externí odkaz:
http://arxiv.org/abs/2411.16767
Human Mesh Recovery (HMR) is an important yet challenging problem with applications across various domains including motion capture, augmented reality, and biomechanics. Accurately predicting human pose parameters from a single image remains a challe
Externí odkaz:
http://arxiv.org/abs/2411.11214
Motion capture technologies have transformed numerous fields, from the film and gaming industries to sports science and healthcare, by providing a tool to capture and analyze human movement in great detail. The holy grail in the topic of monocular gl
Externí odkaz:
http://arxiv.org/abs/2411.10582
Vision-language-action (VLA) models represent a promising direction for developing general-purpose robotic systems, demonstrating the ability to combine visual understanding, language comprehension, and action generation. However, systematic evaluati
Externí odkaz:
http://arxiv.org/abs/2411.05821
The advent of Large Language Models (LLMs) have shown promise in various creative domains, including culinary arts. However, many LLMs still struggle to deliver the desired level of culinary creativity, especially when tasked with adapting recipes to
Externí odkaz:
http://arxiv.org/abs/2411.01996
Autor:
Sohn, Jiwoong, Park, Yein, Yoon, Chanwoong, Park, Sihyeon, Hwang, Hyeon, Sung, Mujeen, Kim, Hyunjae, Kang, Jaewoo
Large language models (LLM) hold significant potential for applications in biomedicine, but they struggle with hallucinations and outdated knowledge. While retrieval-augmented generation (RAG) is generally employed to address these issues, it also ha
Externí odkaz:
http://arxiv.org/abs/2411.00300