4.5k citations · 5.1k across the 23 of their papers we have counts for
25 papers
Towards Mitigating Hallucination in Large Language Models via Self-Reflection
Ziwei Ji, Tiezheng Yu, Yan Xu +3
Large language models (LLMs) have shown promise for generative and knowledge-intensive tasks including question-answering (QA) tasks. However, the practical deployment still faces…
Improving Query-Focused Meeting Summarization with Query-Relevant Knowledge
Tiezheng Yu, Ziwei Ji, Pascale Fung
Query-Focused Meeting Summarization (QFMS) aims to generate a summary of a given meeting transcript conditioned upon a query. The main challenges for QFMS are the long input text l…
InstructAlign: High-and-Low Resource Language Alignment via Continual Crosslingual Instruction Tuning
Samuel Cahyawijaya, Holy Lovenia, Tiezheng Yu +2
Large language models (LLMs) that are tuned with instructions have demonstrated remarkable capabilities in various tasks and languages. However, their ability to generalize to unde…
A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee +10
This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of…
NusaCrowd: Open Source Initiative for Indonesian NLP Resources
Samuel Cahyawijaya, Holy Lovenia, Alham Fikri Aji +44
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Thro…
RHO (): Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding
Ziwei Ji, Zihan Liu, Nayeon Lee +4
Dialogue systems can leverage large pre-trained language models and knowledge to generate fluent and informative responses. However, these models are still prone to produce halluci…
Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness
Caner Hazirbas, Yejin Bang, Tiezheng Yu +9
Developing robust and fair AI systems require datasets with comprehensive set of labels that can help ensure the validity and legitimacy of relevant measurements. Recent efforts, t…
Enabling Classifiers to Make Judgements Explicitly Aligned with Human Values
Yejin Bang, Tiezheng Yu, Andrea Madotto +3
Many NLP classification tasks, such as sexism/racism detection or toxicity detection, are based on human values. Yet, human values can vary under diverse cultural conditions. There…
Kaggle Competition: Cantonese Audio-Visual Speech Recognition for In-car Commands
Wenliang Dai, Samuel Cahyawijaya, Tiezheng Yu +2
With the rise of deep learning and intelligent vehicles, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-ca…
NeuS: Neutral Multi-News Summarization for Mitigating Framing Bias
Nayeon Lee, Yejin Bang, Tiezheng Yu +2
Media news framing bias can increase political polarization and undermine civil society. The need for automatic mitigation methods is therefore growing. We propose a new task, a ne…
Towards Answering Open-ended Ethical Quandary Questions
Yejin Bang, Nayeon Lee, Tiezheng Yu +10
Considerable advancements have been made in various NLP tasks based on the impressive power of large language models (LLMs) and many NLP applications are deployed in our daily live…
SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study
Samuel Cahyawijaya, Tiezheng Yu, Zihan Liu +4
Self-supervised pre-training methods have brought remarkable breakthroughs in the understanding of text, image, and speech. Recent developments in genomics has also adopted these p…
Survey of Hallucination in Natural Language Generation
Ziwei Ji, Nayeon Lee, Rita Frieske +10
Natural Language Generation (NLG) has improved exponentially in recent years thanks to the development of sequence-to-sequence deep learning technologies such as Transformer-based…
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
Tiezheng Yu, Rita Frieske, Peng Xu +9
Automatic speech recognition (ASR) on low resource languages improves the access of linguistic minorities to technological advantages provided by artificial intelligence (AI). In t…
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition
Wenliang Dai, Samuel Cahyawijaya, Tiezheng Yu +10
With the rise of deep learning and intelligent vehicle, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-car…
ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation
Holy Lovenia, Samuel Cahyawijaya, Genta Indra Winata +11
Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken la…
Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization
Tiezheng Yu, Wenliang Dai, Zihan Liu +1
Multimodal abstractive summarization (MAS) models that summarize videos (vision modality) and their corresponding transcripts (text modality) are able to extract the essential info…
Improve Query Focused Abstractive Summarization by Incorporating Answer Relevance
Dan Su, Tiezheng Yu, Pascale Fung
Query focused summarization (QFS) models aim to generate summaries from source documents that can answer the given query. Most previous work on QFS only considers the query relevan…
AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization
Tiezheng Yu, Zihan Liu, Pascale Fung
State-of-the-art abstractive summarization models generally rely on extensive labeled data, which lowers their generalization ability on domains where such data are not available.…
CrossNER: Evaluating Cross-Domain Named Entity Recognition
Zihan Liu, Yan Xu, Tiezheng Yu +5
Cross-domain named entity recognition (NER) models are able to cope with the scarcity issue of NER samples in target domains. However, most of the existing NER benchmarks lack doma…
Dimsum @LaySumm 20: BART-based Approach for Scientific Document Summarization
Tiezheng Yu, Dan Su, Wenliang Dai +1
Lay summarization aims to generate lay summaries of scientific papers automatically. It is an essential task that can increase the relevance of science for all of society. In this…
Modality-Transferable Emotion Embeddings for Low-Resource Multimodal Emotion Recognition
Wenliang Dai, Zihan Liu, Tiezheng Yu +1
Despite the recent achievements made in the multi-modal emotion recognition task, two problems still exist and have not been well investigated: 1) the relationship between differen…
Multi-hop Question Generation with Graph Convolutional Network
Dan Su, Yan Xu, Wenliang Dai +3
Multi-hop Question Generation (QG) aims to generate answer-related questions by aggregating and reasoning over multiple scattered evidence from different paragraphs. It is a more c…
CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Management
Dan Su, Yan Xu, Tiezheng Yu +3
We present CAiRE-COVID, a real-time question answering (QA) and multi-document summarization system, which won one of the 10 tasks in the Kaggle COVID-19 Open Research Dataset Chal…