Yi Cai

TSDG: Content-aware Neural Response Generation with Two-stage Decoding Process

2020

Neural response generative models have achieved remarkable progress in recent years but tend to yield irrelevant and uninformative responses. One of the reasons is that encoderdecoder based models always use a single decoder to generate …

Fast Extraction of Word Embedding from Q-contexts

2021

The notion of word embedding plays a fundamental role in natural language processing (NLP). However, pre-training word embedding for very large-scale vocabulary is computationally challenging for most existing methods. In this work, we show that …

Diverse Distractor Generation for Constructing High-Quality Multiple Choice Questions

2021 · IEEE/ACM Transactions on Audio Speech and Language Processing

Distractor generation task aims to generate incorrect options (i.e., distractors) for multiple choice questions from an article.Existing methods for this task often utilize a standard encoder-decoder framework. However, these methods often tend to generate semantically …

Improving Named Entity Recognition via Bridge-based Domain Adaptation

2023

Recent studies have shown remarkable success in cross-domain named entity recognition (cross-domain NER). Despite the promising results, existing methods mainly utilize pre-training language models like BERT to represent words. As such, the original chaotic representations …

Few-Shot Joint Multimodal Entity-Relation Extraction via Knowledge-Enhanced Cross-modal Prompt Model

2024

Joint Multimodal Entity-Relation Extraction (JMERE) is a challenging task that aims to extract entities and their relations from textimage pairs in social media posts. Existing methods for JMERE require large amounts of labeled data. However, …

Pruning Self-Attention With Local and Syntactic Dependencies for Aspect Sentiment Triplet Extraction

2025 · IEEE Transactions on Audio Speech and Language Processing

Aspect-based sentiment triple extraction (ASTE) is a demanding and emerging subtask of aspect-based sentiment analysis (ABSA). The primary objective of ASTE is to extract aspect and opinion terms and their corresponding sentiment polarities from a …

ExpStar: Towards Automatic Commentary Generation for Multi-discipline Scientific Experiments

2025

Experiment commentary is crucial in describing the experimental procedures, delving into underlying scientific principles, and incorporating content-related safety guidelines. In practice, human teachers rely heavily on subject-specific expertise and invest significant time preparing such commentary. …