43 citations · 67 across the 29 of their papers we have counts for
11 papers · 1 filter
Picking the Underused Heads: A Network Pruning Perspective of Attention Head Selection for Fusing Dialogue Coreference Information
Zhengyuan Liu, Nancy F. Chen
The Transformer-based models with the multi-head self-attention mechanism are widely used in natural language processing, and provide state-of-the-art results. While the pre-traine…
Multi-label and Multi-target Sampling of Machine Annotation for Computational Stance Detection
Zhengyuan Liu, Hai Leong Chieu, Nancy F. Chen
Data collection from manual labeling provides domain-specific and task-aligned supervision for data-driven approaches, and a critical mass of well-annotated resources is required t…
CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation
Minzhi Li, Taiwei Shi, Caleb Ziems +4
Annotated data plays a critical role in Natural Language Processing (NLP) in training models and evaluating their performance. Given recent developments in Large Language Models (L…
Instructive Dialogue Summarization with Query Aggregations
Bin Wang, Zhengyuan Liu, Nancy F. Chen
Conventional dialogue summarization methods directly generate summaries and do not consider user's specific interests. This poses challenges in cases where the users are more focus…
PromptSum: Parameter-Efficient Controllable Abstractive Summarization
Mathieu Ravaut, Hailin Chen, Ruochen Zhao +3
Prompt tuning (PT), a parameter-efficient technique that only tunes the additional prompt embeddings while keeping the backbone pre-trained language model (PLM) frozen, has shown p…
Prompter: Zero-shot Adaptive Prefixes for Dialogue State Tracking Domain Adaptation
Taha Aksu, Min-Yen Kan, Nancy F. Chen
A challenge in the Dialogue State Tracking (DST) field is adapting models to new domains without using any supervised data, zero-shot domain adaptation. Parameter-Efficient Transfe…
Multiple output samples per input in a single-output Gaussian process
Jeremy H. M. Wong, Huayun Zhang, Nancy F. Chen
The standard Gaussian Process (GP) only considers a single output sample per input in the training set. Datasets for subjective tasks, such as spoken language assessment, may be an…
Guiding Computational Stance Detection with Expanded Stance Triangle Framework
Zhengyuan Liu, Yong Keong Yap, Hai Leong Chieu +1
Stance detection determines whether the author of a piece of text is in favor of, against, or neutral towards a specified target, and can be used to gain valuable insights into soc…
Adapter-TST: A Parameter Efficient Method for Multiple-Attribute Text Style Transfer
Zhiqiang Hu, Roy Ka-Wei Lee, Nancy F. Chen
Adapting a large language model for multiple-attribute text style transfer via fine-tuning can be challenging due to the significant amount of computational resources and labeled d…
Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation
Xuan Long Do, Bowei Zou, Shafiq Joty +4
Conversational Question Generation (CQG) is a critical task for machines to assist humans in fulfilling their information needs through conversations. The task is generally cast in…
Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models
Ratish Puduppully, Anoop Kunchukuttan, Raj Dabre +2
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 si…