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Ekapol Chuangsuwanich

19 accepted papers

2025

Towards Better Understanding of Program-of-Thought Reasoning in Cross-Lingual and Multilingual Environments

Patomporn Payoungkhamdee, Pume Tuchinda, Jinheon Baek, Samuel Cahyawijaya, Can Udomcharoenchaikit, Potsawee Manakul +3
ACL 2025finding

Multi-step reasoning is essential for large language models (LLMs), yet multilingual performance remains challenging. While Chain-of-Thought (CoT) prompting improves reasoning, it struggles with non-English languages due to the entanglement of reasoning and execution. Program-of-Thought (PoT) prompt…

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2024

An Empirical Study of Multilingual Reasoning Distillation for Question Answering

Patomporn Payoungkhamdee, Peerat Limkonchotiwat, Jinheon Baek, Potsawee Manakul, Can Udomcharoenchaikit, Ekapol Chuangsuwanich +1
EMNLP 2024main

Reasoning is one crucial capability in Large Language Models (LLMs), allowing them to perform complex tasks such as solving math problems and multi-step planning. While reasoning capability can emerge in larger models, smaller ones usually have to rely on distillation to transfer this capability fro…

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2024

Attribute-Aware Amplification of Facial Feature Sequences for Facial Emotion Recognition

Tagon Sompong, Chawan Piansaddhayanon, Ekapol Chuangsuwanich
ICASSP 2024accepted

Many works have been proposed to automatically recognize facial human emotions, yet distinguishing subtle emotions still remains a challenge. However, just amplifying these facial movements as a whole does not accurately reflect the actual expressions as action intensity is different for each facial…

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2024

Efficient Overshadowed Entity Disambiguation by Mitigating Shortcut Learning

Panuthep Tasawong, Peerat Limkonchotiwat, Potsawee Manakul, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
EMNLP 2024main

Entity disambiguation (ED) is crucial in natural language processing (NLP) for tasks such as question-answering and information extraction. A major challenge in ED is handling overshadowed entities—uncommon entities sharing mention surfaces with common entities. The current approach to enhance perfo…

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2024

Identifying and Mitigating Annotation Bias in Natural Language Understanding using Causal Mediation Analysis

Sitiporn Sae Lim, Can Udomcharoenchaikit, Peerat Limkonchotiwat, Ekapol Chuangsuwanich, Sarana Nutanong
ACL 2024findings

NLU models have achieved promising results on standard benchmarks. Despite state-of-the-art accuracy, analysis reveals that many models make predictions using annotation bias rather than the properties we intend the model to learn. Consequently, these models perform poorly on out-of-distribution dat…

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2024

Learning Job Title Representation from Job Description Aggregation Network

Napat Laosaengpha, Thanit Tativannarat, Chawan Piansaddhayanon, Attapol Rutherford, Ekapol Chuangsuwanich
ACL 2024findings

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 and diverse content within. Thus, we propose an al…

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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…

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2024

MrRank: Improving Question Answering Retrieval System through Multi-Result Ranking Model

Danupat Khamnuansin, Tawunrat Chalothorn, Ekapol Chuangsuwanich
ACL 2024findings

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 deficiencies, posing a performance bottleneck. Given the ex…

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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…

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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…

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2023

Zero-guidance Segmentation Using Zero Segment Labels

Pitchaporn Rewatbowornwong, Nattanat Chatthee, Ekapol Chuangsuwanich, Supasorn Suwajanakorn
ICCV 2023poster

The joint visual-language model CLIP has enabled new and exciting applications, such as 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 segments without any user guidance in the form of text…

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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…

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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,…

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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…

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2021

Reducing Spelling Inconsistencies in Code-Switching ASR Using Contextualized CTC Loss

Burin Naowarat, Thananchai Kongthaworn, Korrawe Karunratanakul, Sheng Hui Wu, Ekapol Chuangsuwanich
ICASSP 2021accepted

Code-Switching (CS) remains a challenge for Automatic Speech Recognition (ASR), especially character-based models. With the combined choice of characters from multiple languages, the out-come from character-based models suffers from phoneme duplication, resulting in language-inconsistent spellings.…

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2021

Robust Fragment-Based Framework for Cross-lingual Sentence Retrieval

Nattapol Trijakwanich, Peerat Limkonchotiwat, Raheem Sarwar, Wannaphong Phatthiyaphaibun, Ekapol Chuangsuwanich, Sarana Nutanong
EMNLP 2021finding

Cross-lingual Sentence Retrieval (CLSR) aims at retrieving parallel sentence pairs that are translations of each other from a multilingual set of comparable documents. The retrieved parallel sentence pairs can be used in other downstream NLP tasks such as machine translation and cross-lingual word s…

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2021

Set Prediction in the Latent Space

Konpat Preechakul, Chawan Piansaddhayanon, Burin Naowarat, Tirasan Khandhawit, Sira Sriswasdi, Ekapol Chuangsuwanich
NeurIPS 2021poster

Set prediction tasks require the matching between predicted set and ground truth set in order to propagate the gradient signal. Recent works have performed this matching in the original feature space thus requiring predefined distance functions. We propose a method for learning the distance function…

Cited by 6Source ↗PDF ↗code ↗Scholar ↗
2016

Multilingual data selection for training stacked bottleneck features

Ekapol Chuangsuwanich, Yu Zhang, James R. Glass
ICASSP 2016accepted

Deep Neural Networks (DNNs) trained on multilingual data have proven useful for improving speech recognition in languages with limited resources. In this framework, data from rich resource languages are pooled together to train a single system and then adapted to a new language. However, data from a…

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2016

Prediction-adaptation-correction recurrent neural networks for low-resource language speech recognition

Yu Zhang, Ekapol Chuangsuwanich, James R. Glass, Dong Yu
ICASSP 2016accepted

In this paper, we investigate the use of prediction-adaptation-correction recurrent neural networks (PAC-RNNs) for low-resource speech recognition. A PAC-RNN is comprised of a pair of neural networks in which a correction network uses auxiliary information given by a prediction network to help estim…

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