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Wuttikorn Ponwitayarat

6 accepted papers

2024

McCrolin: Multi-consistency Cross-lingual Training for Retrieval Question Answering

Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Lalita Lowphansirikul, Potsawee Manakul, Can Udomcharoenchaikit, Ekapol Chuangsuwanich +1
EMNLP 2024finding

Automated question answering (QA) systems are increasingly relying on robust cross-lingual retrieval to identify and utilize information from multilingual sources, ensuring comprehensive and contextually accurate responses. Existing approaches often struggle with consistency across multiple language…

Cited by 5Source ↗PDF ↗Scholar ↗
2024

Space Decomposition for Sentence Embedding

Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Ekapol Chuangsuwanich, Sarana Nutanong
ACL 2024findings

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 annotation guidelines, we found that the score in the rang…

Cited by 1Source ↗PDF ↗code ↗Scholar ↗
2023

Typo-Robust Representation Learning for Dense Retrieval

Panuthep Tasawong, Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
ACL 2023short

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 queries is minimizing the representations discrepan…

Cited by 8Source ↗PDF ↗code ↗Scholar ↗
2022

CL-ReLKT: Cross-lingual Language Knowledge Transfer for Multilingual Retrieval Question Answering

Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
NAACL 2022findings

Cross-Lingual Retrieval Question Answering (CL-ReQA) is concerned with retrieving answer documents or passages to a question written in a different language. A common approach to CL-ReQA is to create a multilingual sentence embedding space such that question-answer pairs across different languages a…

Cited by 9Source ↗PDF ↗code ↗Scholar ↗
2022

ConGen: Unsupervised Control and Generalization Distillation For Sentence Representation

Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Lalita Lowphansirikul, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
EMNLP 2022finding

Sentence representations are essential in many NLP tasks operating at the sentence level.Recently, research attention has shifted towards learning how to represent sentences without any annotations, i.e., unsupervised representation learning. Despite the benefit of training without supervised data,…

Cited by 8Source ↗PDF ↗code ↗Scholar ↗
2022

Mitigating Spurious Correlation in Natural Language Understanding with Counterfactual Inference

Can Udomcharoenchaikit, Wuttikorn Ponwitayarat, Patomporn Payoungkhamdee, Kanruethai Masuk, Weerayut Buaphet, Ekapol Chuangsuwanich +1
EMNLP 2022main

Despite their promising results on standard benchmarks, NLU models are still prone to make predictions based on shortcuts caused by unintended bias in the dataset. For example, an NLI model may use lexical overlap as a shortcut to make entailment predictions due to repetitive data generation pattern…

Cited by 13Source ↗PDF ↗Scholar ↗