Zobrazeno 1 - 10
of 416
pro vyhledávání: '"A. Chuangsuwanich"'
Autor:
Chuangsuwanich, Thanadet, Nongpiur, Monisha E., Braeu, Fabian A., Tun, Tin A., Thiery, Alexandre, Perera, Shamira, Ho, Ching Lin, Buist, Martin, Barbastathis, George, Aung, Tin, Girard, Michaël J. A.
Objective. (1) To assess whether neural tissue structure and biomechanics could predict functional loss in glaucoma; (2) To evaluate the importance of biomechanics in making such predictions. Design, Setting and Participants. We recruited 238 glaucom
Externí odkaz:
http://arxiv.org/abs/2406.14988
Autor:
Laosaengpha, Napat, Tativannarat, Thanit, Piansaddhayanon, Chawan, Rutherford, Attapol, Chuangsuwanich, Ekapol
Learning job title representation is a vital process for developing automatic human resource tools. To do so, existing methods primarily rely on learning the title representation through skills extracted from the job description, neglecting the rich
Externí odkaz:
http://arxiv.org/abs/2406.08055
Diffusion-based speech enhancement has shown promising results, but can suffer from a slower inference time. Initializing the diffusion process with the enhanced audio generated by a regression-based model can be used to reduce the computational step
Externí odkaz:
http://arxiv.org/abs/2406.06139
Large Language Models (LLMs) often struggle with hallucinations and outdated information. To address this, Information Retrieval (IR) systems can be employed to augment LLMs with up-to-date knowledge. However, existing IR techniques contain deficienc
Externí odkaz:
http://arxiv.org/abs/2406.05733
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:
Rewatbowornwong, Pitchaporn, Chatthee, Nattanat, Chuangsuwanich, Ekapol, Suwajanakorn, Supasorn
CLIP has enabled new and exciting joint vision-language applications, one of which is open-vocabulary segmentation, which can locate any segment given an arbitrary text query. In our research, we ask whether it is possible to discover semantic segmen
Externí odkaz:
http://arxiv.org/abs/2303.13396
Autor:
Braeu, Fabian A., Chuangsuwanich, Thanadet, Tun, Tin A., Perera, Shamira A., Husain, Rahat, Kadziauskiene, Aiste, Schmetterer, Leopold, Thiéry, Alexandre H., Barbastathis, George, Aung, Tin, Girard, Michaël J. A.
$\bf{Purpose}$: To describe the 3D structural changes in both connective and neural tissues of the optic nerve head (ONH) that occur concurrently at different stages of glaucoma using traditional and AI-driven approaches. $\bf{Methods}$: We included
Externí odkaz:
http://arxiv.org/abs/2301.02837