1 code implementation • Findings (NAACL) 2022 • Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
A common approach to CL-ReQA is to create a multilingual sentence embedding space such that question-answer pairs across different languages are close to each other.
1 code implementation • Findings (ACL) 2022 • Weerayut Buaphet, Can Udomcharoenchaikit, Peerat Limkonchotiwat, Attapol Rutherford, Sarana Nutanong
Our work, to the best of our knowledge, presents the largest non-English N-NER dataset and the first non-English one with fine-grained classes.
1 code implementation • 24 Mar 2024 • Wannaphong Phatthiyaphaibun, Surapon Nonesung, Patomporn Payoungkhamdee, Peerat Limkonchotiwat, Can Udomcharoenchaikit, Jitkapat Sawatphol, Chompakorn Chaksangchaichot, Ekapol Chuangsuwanich, Sarana Nutanong
Our model is based on SEA-LION and a collection of instruction following datasets.
1 code implementation • 7 Dec 2023 • Wannaphong Phatthiyaphaibun, Korakot Chaovavanich, Charin Polpanumas, Arthit Suriyawongkul, Lalita Lowphansirikul, Pattarawat Chormai, Peerat Limkonchotiwat, Thanathip Suntorntip, Can Udomcharoenchaikit
It provides a wide range of software, models, and datasets for Thai language.
1 code implementation • 6 Nov 2023 • Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Lalita Lowphansirikul, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
In this paper, we propose a framework called Self-supervised Cross-View Training (SCT) to narrow the performance gap between large and small PLMs.
1 code implementation • 17 Jun 2023 • Panuthep Tasawong, Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
One of the main challenges of dense retrieval in real-world settings is the handling of queries containing misspelled words.