Zobrazeno 1 - 10
of 137
pro vyhledávání: '"NUTANONG, SARANA"'
Authorship verification (AV) aims to identify whether a pair of texts has the same author. We address the challenge of evaluating AV models' robustness against topic shifts. The conventional evaluation assumes minimal topic overlap between training a
Externí odkaz:
http://arxiv.org/abs/2407.19164
Determining sentence pair similarity is crucial for various NLP tasks. A common technique to address this is typically evaluated on a continuous semantic textual similarity scale from 0 to 5. However, based on a linguistic observation in STS annotati
Externí odkaz:
http://arxiv.org/abs/2406.03125
Autor:
Phatthiyaphaibun, Wannaphong, Nonesung, Surapon, Payoungkhamdee, Patomporn, Limkonchotiwat, Peerat, Udomcharoenchaikit, Can, Sawatphol, Jitkapat, Chaksangchaichot, Chompakorn, Chuangsuwanich, Ekapol, Nutanong, Sarana
This technical report describes the development of WangchanLion, an instruction fine-tuned model focusing on Machine Reading Comprehension (MRC) in the Thai language. Our model is based on SEA-LION and a collection of instruction following datasets.
Externí odkaz:
http://arxiv.org/abs/2403.16127
Autor:
Limkonchotiwat, Peerat, Ponwitayarat, Wuttikorn, Lowphansirikul, Lalita, Udomcharoenchaikit, Can, Chuangsuwanich, Ekapol, Nutanong, Sarana
Self-supervised sentence representation learning is the task of constructing an embedding space for sentences without relying on human annotation efforts. One straightforward approach is to finetune a pretrained language model (PLM) with a representa
Externí odkaz:
http://arxiv.org/abs/2311.03228
Autor:
Tasawong, Panuthep, Ponwitayarat, Wuttikorn, Limkonchotiwat, Peerat, Udomcharoenchaikit, Can, Chuangsuwanich, Ekapol, Nutanong, Sarana
Dense retrieval is a basic building block of information retrieval applications. One of the main challenges of dense retrieval in real-world settings is the handling of queries containing misspelled words. A popular approach for handling misspelled q
Externí odkaz:
http://arxiv.org/abs/2306.10348
Autor:
Phatthiyaphaibun, Wannaphong, Chaksangchaichot, Chompakorn, Limkonchotiwat, Peerat, Chuangsuwanich, Ekapol, Nutanong, Sarana
Recently, Automatic Speech Recognition (ASR), a system that converts audio into text, has caught a lot of attention in the machine learning community. Thus, a lot of publicly available models were released in HuggingFace. However, most of these ASR m
Externí odkaz:
http://arxiv.org/abs/2208.04799
Transformer-based language models, more specifically BERT-based architectures have achieved state-of-the-art performance in many downstream tasks. However, for a relatively low-resource language such as Thai, the choices of models are limited to trai
Externí odkaz:
http://arxiv.org/abs/2101.09635
The primary objective of our work is to build a large-scale English-Thai dataset for machine translation. We construct an English-Thai machine translation dataset with over 1 million segment pairs, curated from various sources, namely news, Wikipedia
Externí odkaz:
http://arxiv.org/abs/2007.03541
With the recent technological innovation, unmanned aerial vehicles, known as drones, have found numerous applications including package and parcel delivery for shippers. Drone delivery offers benefits over conventional ground-based vehicle delivery i
Externí odkaz:
http://arxiv.org/abs/2002.03118
Publikováno v:
2019 IEEE 90th Vehicular Technology Conference: VTC2019-Fall
Recently, an unmanned aerial vehicle (UAV), as known as drone, has become an alternative means of package delivery. Although the drone delivery scheduling has been studied in recent years, most existing models are formulated as a single objective opt
Externí odkaz:
http://arxiv.org/abs/1908.07406