Search Results for author: Ai Ti Aw

Found 29 papers, 7 papers with code

Automatic True/False Question Generation for Educational Purpose

no code implementations NAACL (BEA) 2022 Bowei Zou, Pengfei Li, Liangming Pan, Ai Ti Aw

In field of teaching, true/false questioning is an important educational method for assessing students’ general understanding of learning materials.

Fact Verification Question Generation +2

Singlish Message Paraphrasing: A Joint Task of Creole Translation and Text Normalization

no code implementations COLING 2022 Zhengyuan Liu, Shikang Ni, Ai Ti Aw, Nancy F. Chen

In this work, we introduce a joint paraphrasing task of creole translation and text normalization of Singlish messages, which can shed light on how to process other language varieties and dialects.

Stance Detection Text Normalization +1

Beyond Classification: Towards Speech Emotion Reasoning with Multitask AudioLLMs

no code implementations7 Jun 2025 Wenyu Zhang, Yingxu He, Geyu Lin, Zhuohan Liu, Shuo Sun, Bin Wang, Xunlong Zou, Jeremy H. M. Wong, Qiongqiong Wang, Hardik B. Sailor, Nancy F. Chen, Ai Ti Aw

Audio Large Language Models (AudioLLMs) have achieved strong results in semantic tasks like speech recognition and translation, but remain limited in modeling paralinguistic cues such as emotion.

Emotion Recognition speech-recognition +1

Improving Multilingual Social Media Insights: Aspect-based Comment Analysis

no code implementations29 May 2025 Longyin Zhang, Bowei Zou, Ai Ti Aw

The inherent nature of social media posts, characterized by the freedom of language use with a disjointed array of diverse opinions and topics, poses significant challenges to downstream NLP tasks such as comment clustering, comment summarization, and social media opinion analysis.

Contextual Paralinguistic Data Creation for Multi-Modal Speech-LLM: Data Condensation and Spoken QA Generation

no code implementations19 May 2025 Qiongqiong Wang, Hardik B. Sailor, Tianchi Liu, Ai Ti Aw

Current speech-LLMs exhibit limited capability in contextual reasoning alongside paralinguistic understanding, primarily due to the lack of Question-Answer (QA) datasets that cover both aspects.

Dataset Generation

AdaCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Chain-of-Thought

no code implementations27 Jan 2025 Xin Huang, Tarun Kumar Vangani, Zhengyuan Liu, Bowei Zou, Ai Ti Aw

Large language models have shown impressive multilingual capabilities through pretraining on diverse corpora.

Machine Translation

MERaLiON-AudioLLM: Bridging Audio and Language with Large Language Models

no code implementations13 Dec 2024 Yingxu He, Zhuohan Liu, Shuo Sun, Bin Wang, Wenyu Zhang, Xunlong Zou, Nancy F. Chen, Ai Ti Aw

We introduce MERaLiON-AudioLLM (Multimodal Empathetic Reasoning and Learning in One Network), the first speech-text model tailored for Singapore's multilingual and multicultural landscape.

speech-recognition Speech Recognition

MoWE-Audio: Multitask AudioLLMs with Mixture of Weak Encoders

no code implementations10 Sep 2024 Wenyu Zhang, Shuo Sun, Bin Wang, Xunlong Zou, Zhuohan Liu, Yingxu He, Geyu Lin, Nancy F. Chen, Ai Ti Aw

The rapid advancements in large language models (LLMs) have significantly enhanced natural language processing capabilities, facilitating the development of AudioLLMs that process and understand speech and audio inputs alongside text.

Evidence-based Interpretable Open-domain Fact-checking with Large Language Models

no code implementations10 Dec 2023 Xin Tan, Bowei Zou, Ai Ti Aw

Universal fact-checking systems for real-world claims face significant challenges in gathering valid and sufficient real-time evidence and making reasoned decisions.

Fact Checking valid

Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models

1 code implementation22 May 2023 Ratish Puduppully, Anoop Kunchukuttan, Raj Dabre, Ai Ti Aw, Nancy F. Chen

This study investigates machine translation between related languages i. e., languages within the same family that share linguistic characteristics such as word order and lexical similarity.

Machine Translation Translation

Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation

1 code implementation4 May 2023 Xuan Long Do, Bowei Zou, Shafiq Joty, Anh Tai Tran, Liangming Pan, Nancy F. Chen, Ai Ti Aw

In addition, we propose Conv-Distinct, a novel evaluation metric for CQG, to evaluate the diversity of the generated conversation from a context.

Question Generation Question-Generation +1

CoHS-CQG: Context and History Selection for Conversational Question Generation

1 code implementation COLING 2022 Xuan Long Do, Bowei Zou, Liangming Pan, Nancy F. Chen, Shafiq Joty, Ai Ti Aw

While previous studies mainly focus on how to model the flow and alignment of the conversation, there has been no thorough study to date on which parts of the context and history are necessary for the model.

Question Generation Question-Generation +1

Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Model

1 code implementation31 May 2022 Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw

Numerous recent work on unsupervised machine translation (UMT) implies that competent unsupervised translations of low-resource and unrelated languages, such as Nepali or Sinhala, are only possible if the model is trained in a massive multilingual environment, where these low-resource languages are mixed with high-resource counterparts.

Disentanglement Translation +1

Improving Lexical Embeddings for Robust Question Answering

no code implementations28 Feb 2022 Weiwen Xu, Bowei Zou, Wai Lam, Ai Ti Aw

Recent techniques in Question Answering (QA) have gained remarkable performance improvement with some QA models even surpassed human performance.

Question Answering

Coherent and Concise Radiology Report Generation via Context Specific Image Representations and Orthogonal Sentence States

no code implementations NAACL 2021 Litton J Kurisinkel, Ai Ti Aw, Nancy F Chen

Neural models for text generation are often designed in an end-to-end fashion, typically with zero control over intermediate computations, limiting their practical usability in downstream applications.

Diversity Informativeness +2

Addressing the Vulnerability of NMT in Input Perturbations

1 code implementation NAACL 2021 Weiwen Xu, Ai Ti Aw, Yang Ding, Kui Wu, Shafiq Joty

Neural Machine Translation (NMT) has achieved significant breakthrough in performance but is known to suffer vulnerability to input perturbations.

fr-en Machine Translation +2

Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks

no code implementations COLING 2020 Zhengyuan Liu, Pavitra Krishnaswamy, Ai Ti Aw, Nancy Chen

While neural approaches have achieved significant improvement in machine comprehension tasks, models often work as a black-box, resulting in lower interpretability, which requires special attention in domains such as healthcare or education.

Active Learning Dialogue Generation +2

Cross-model Back-translated Distillation for Unsupervised Machine Translation

1 code implementation3 Jun 2020 Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen, Wu Kui, Ai Ti Aw

Recent unsupervised machine translation (UMT) systems usually employ three main principles: initialization, language modeling and iterative back-translation, though they may apply them differently.

Denoising Diversity +4

Data Diversification: A Simple Strategy For Neural Machine Translation

2 code implementations NeurIPS 2020 Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw

Our method achieves state-of-the-art BLEU scores of 30. 7 and 43. 7 in the WMT'14 English-German and English-French translation tasks, respectively.

Knowledge Distillation Machine Translation +2

Sentiment Aware Neural Machine Translation

no code implementations WS 2019 Chenglei Si, Kui Wu, Ai Ti Aw, Min-Yen Kan

We conducted tests with both sentiment and non-sentiment bearing contexts to examine the effectiveness of our methods.

Machine Translation NMT +3

Topic-aware Pointer-Generator Networks for Summarizing Spoken Conversations

no code implementations3 Oct 2019 Zhengyuan Liu, Angela Ng, Sheldon Lee, Ai Ti Aw, Nancy F. Chen

Such linguistic characteristics of dialogue topics make sentence-level extractive summarization approaches used in spoken documents ill-suited for summarizing conversations.

Conversation Summarization Extractive Summarization +2

Cannot find the paper you are looking for? You can Submit a new open access paper.