4 citations · 12 across the 12 of their papers we have counts for
22 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…