Zobrazeno 1 - 10
of 21 190
pro vyhledávání: '"Kim So Eun"'
Medical vision-language model models often struggle with generating accurate quantitative measurements in radiology reports, leading to hallucinations that undermine clinical reliability. We introduce FactCheXcker, a modular framework that de-halluci
Externí odkaz:
http://arxiv.org/abs/2411.18672
Autor:
Mendez, Jeremy, Kim, Yae Eun, Chowdhury, Nafisah, Tziranis, Alexios, Le, Phuong, Tran, Angela, Moron, Rocio, Rogers, Julia, Chowdhury, Aohona, Wall, Elijah, Arroyo-Currás, Netzahualcóyotl, Lukeman, Philip
Electrochemical biosensors ("E-AB" or "E-DNA" type sensors) that utilize square-wave voltammetry originated in academic labs with a few standard experimental configurations for the electrochemical cell and data analysis. We report here on adaptations
Externí odkaz:
http://arxiv.org/abs/2410.24110
Random forest (RF) stands out as a highly favored machine learning approach for classification problems. The effectiveness of RF hinges on two key factors: the accuracy of individual trees and the diversity among them. In this study, we introduce a n
Externí odkaz:
http://arxiv.org/abs/2410.19022
Autor:
Li, Jianwei, Kim, Jung-Eun
As large language models (LLMs) are overwhelmingly more and more integrated into various applications, ensuring they generate safe and aligned responses is a pressing need. Previous research on alignment has largely focused on general instruction-fol
Externí odkaz:
http://arxiv.org/abs/2410.10862
Autor:
Kim, To Eun, Diaz, Fernando
Many language models now enhance their responses with retrieval capabilities, leading to the widespread adoption of retrieval-augmented generation (RAG) systems. However, despite retrieval being a core component of RAG, much of the research in this a
Externí odkaz:
http://arxiv.org/abs/2409.11598
Speech-driven 3D facial animation has garnered lots of attention thanks to its broad range of applications. Despite recent advancements in achieving realistic lip motion, current methods fail to capture the nuanced emotional undertones conveyed throu
Externí odkaz:
http://arxiv.org/abs/2408.06010
Autor:
Fang, Xingli, Kim, Jung-Eun
The privacy-preserving approaches to machine learning (ML) models have made substantial progress in recent years. However, it is still opaque in which circumstances and conditions the model becomes privacy-vulnerable, leading to a challenge for ML mo
Externí odkaz:
http://arxiv.org/abs/2407.16164
With the rapid increase in the research, development, and application of neural networks in the current era, there is a proportional increase in the energy needed to train and use models. Crucially, this is accompanied by the increase in carbon emiss
Externí odkaz:
http://arxiv.org/abs/2408.01446
In the field of language modeling, models augmented with retrieval components have emerged as a promising solution to address several challenges faced in the natural language processing (NLP) field, including knowledge grounding, interpretability, an
Externí odkaz:
http://arxiv.org/abs/2407.12982
The dynamics of human-AI communication have been reshaped by language models such as ChatGPT. However, extant research has primarily focused on dyadic communication, leaving much to be explored regarding the dynamics of human-AI communication in grou
Externí odkaz:
http://arxiv.org/abs/2406.19648