Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Lai, Viet Dac"'
FActScore has gained popularity as a metric to estimate the factuality of long-form texts generated by Large Language Models (LLMs) in English. However, there has not been any work in studying the behavior of FActScore in other languages. This paper
Externí odkaz:
http://arxiv.org/abs/2406.19415
Autor:
Lai, Viet Dac, Krumdick, Michael, Lovering, Charles, Reddy, Varshini, Schmidt, Craig, Tanner, Chris
The financial domain frequently deals with large numbers of long documents that are essential for daily operations. Significant effort is put towards automating financial data analysis. However, a persistent challenge, not limited to the finance doma
Externí odkaz:
http://arxiv.org/abs/2406.14394
Autor:
Reddy, Varshini, Koncel-Kedziorski, Rik, Lai, Viet Dac, Krumdick, Michael, Lovering, Charles, Tanner, Chris
For large language models (LLMs) to be effective in the financial domain -- where each decision can have a significant impact -- it is necessary to investigate realistic tasks and data. Financial professionals often interact with documents that are h
Externí odkaz:
http://arxiv.org/abs/2401.06915
Autor:
Nguyen, Thuat, Van Nguyen, Chien, Lai, Viet Dac, Man, Hieu, Ngo, Nghia Trung, Dernoncourt, Franck, Rossi, Ryan A., Nguyen, Thien Huu
The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Along with the progress in natural language processing, LLMs have been fr
Externí odkaz:
http://arxiv.org/abs/2309.09400
Autor:
Lai, Viet Dac, Van Nguyen, Chien, Ngo, Nghia Trung, Nguyen, Thuat, Dernoncourt, Franck, Rossi, Ryan A., Nguyen, Thien Huu
A key technology for the development of large language models (LLMs) involves instruction tuning that helps align the models' responses with human expectations to realize impressive learning abilities. Two major approaches for instruction tuning char
Externí odkaz:
http://arxiv.org/abs/2307.16039
Autor:
Lai, Viet Dac, Salinas, Abel, Tan, Hao, Bui, Trung, Tran, Quan, Yoon, Seunghyun, Deilamsalehy, Hanieh, Dernoncourt, Franck, Nguyen, Thien Huu
Punctuation restoration is an important task in automatic speech recognition (ASR) which aim to restore the syntactic structure of generated ASR texts to improve readability. While punctuated texts are abundant from written documents, the discrepancy
Externí odkaz:
http://arxiv.org/abs/2307.12949
Autor:
Lai, Viet Dac, Ngo, Nghia Trung, Veyseh, Amir Pouran Ben, Man, Hieu, Dernoncourt, Franck, Bui, Trung, Nguyen, Thien Huu
Over the last few years, large language models (LLMs) have emerged as the most important breakthroughs in natural language processing (NLP) that fundamentally transform research and developments in the field. ChatGPT represents one of the most exciti
Externí odkaz:
http://arxiv.org/abs/2304.05613
Autor:
Lai, Viet Dac
Extracting the reported events from text is one of the key research themes in natural language processing. This process includes several tasks such as event detection, argument extraction, role labeling. As one of the most important topics in natural
Externí odkaz:
http://arxiv.org/abs/2210.03419
Mathematical symbols and descriptions appear in various forms across document section boundaries without explicit markup. In this paper, we present a new large-scale dataset that emphasizes extracting symbols and descriptions in scientific documents.
Externí odkaz:
http://arxiv.org/abs/2204.12070
Given the increasing number of livestreaming videos, automatic speech recognition and post-processing for livestreaming video transcripts are crucial for efficient data management as well as knowledge mining. A key step in this process is punctuation
Externí odkaz:
http://arxiv.org/abs/2202.09695