56 citations · 268 across the 22 of their papers we have counts for
22 papers
Continual Zero-Shot Learning through Semantically Guided Generative Random Walks
Wenxuan Zhang, Paul Janson, Kai Yi +2
Learning novel concepts, remembering previous knowledge, and adapting it to future tasks occur simultaneously throughout a human's lifetime. To model such comprehensive abilities,…
M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models
Wenxuan Zhang, Sharifah Mahani Aljunied, Chang Gao +2
Despite the existence of various benchmarks for evaluating natural language processing models, we argue that human exams are a more suitable means of evaluating general intelligenc…
AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative Approach
Jia Guo, Liying Cheng, Wenxuan Zhang +3
Argument mining involves multiple sub-tasks that automatically identify argumentative elements, such as claim detection, evidence extraction, stance classification, etc. However, e…
Zero-Shot Text Classification via Self-Supervised Tuning
Chaoqun Liu, Wenxuan Zhang, Guizhen Chen +4
Existing solutions to zero-shot text classification either conduct prompting with pre-trained language models, which is sensitive to the choices of templates, or rely on large-scal…
Sentiment Analysis in the Era of Large Language Models: A Reality Check
Wenxuan Zhang, Yue Deng, Bing Liu +2
Sentiment analysis (SA) has been a long-standing research area in natural language processing. It can offer rich insights into human sentiments and opinions and has thus seen consi…
Enhancing Few-shot NER with Prompt Ordering based Data Augmentation
Huiming Wang, Liying Cheng, Wenxuan Zhang +2
Recently, data augmentation (DA) methods have been proven to be effective for pre-trained language models (PLMs) in low-resource settings, including few-shot named entity recogniti…
Easy-to-Hard Learning for Information Extraction
Chang Gao, Wenxuan Zhang, Wai Lam +1
Information extraction (IE) systems aim to automatically extract structured information, such as named entities, relations between entities, and events, from unstructured texts. Wh…
Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversations
Yang Deng, Wenxuan Zhang, Yifei Yuan +1
Unlike empathetic dialogues, the system in emotional support conversations (ESC) is expected to not only convey empathy for comforting the help-seeker, but also proactively assist…
Bidirectional Generative Framework for Cross-domain Aspect-based Sentiment Analysis
Yue Deng, Wenxuan Zhang, Sinno Jialin Pan +1
Cross-domain aspect-based sentiment analysis (ABSA) aims to perform various fine-grained sentiment analysis tasks on a target domain by transferring knowledge from a source domain.…
ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions
Deyao Zhu, Jun Chen, Kilichbek Haydarov +3
Asking insightful questions is crucial for acquiring knowledge and expanding our understanding of the world. However, the importance of questioning has been largely overlooked in A…
Product Question Answering in E-Commerce: A Survey
Yang Deng, Wenxuan Zhang, Qian Yu +1
Product question answering (PQA), aiming to automatically provide instant responses to customer's questions in E-Commerce platforms, has drawn increasing attention in recent years.…
From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Model to Pre-trained Machine Reader
Weiwen Xu, Xin Li, Wenxuan Zhang +4
We present Pre-trained Machine Reader (PMR), a novel method for retrofitting pre-trained masked language models (MLMs) to pre-trained machine reading comprehension (MRC) models wit…
Towards Generalizable and Robust Text-to-SQL Parsing
Chang Gao, Bowen Li, Wenxuan Zhang +5
Text-to-SQL parsing tackles the problem of mapping natural language questions to executable SQL queries. In practice, text-to-SQL parsers often encounter various challenging scenar…
A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems
Yang Deng, Wenxuan Zhang, Weiwen Xu +3
Recent years witnessed several advances in developing multi-goal conversational recommender systems (MG-CRS) that can proactively attract users' interests and naturally lead user-e…
A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges
Wenxuan Zhang, Xin Li, Yang Deng +2
As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis (ABSA), aiming to analyze and understand people's opinions at the aspect level, has been at…
Domain-Aware Continual Zero-Shot Learning
Kai Yi, Paul Janson, Wenxuan Zhang +1
Modern visual systems have a wide range of potential applications in vision tasks for natural science research, such as aiding in species discovery, monitoring animals in the wild,…
Aspect Sentiment Quad Prediction as Paraphrase Generation
Wenxuan Zhang, Yang Deng, Xin Li +3
Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years, which typically involves four fundamental sentiment elements, including the aspect category, as…
Multi-hop Inference for Question-driven Summarization
Yang Deng, Wenxuan Zhang, Wai Lam
Question-driven summarization has been recently studied as an effective approach to summarizing the source document to produce concise but informative answers for non-factoid quest…
Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond
Xin Li, Lidong Bing, Wenxuan Zhang +2
Cross-lingual adaptation with multilingual pre-trained language models (mPTLMs) mainly consists of two lines of works: zero-shot approach and translation-based approach, which have…
Answer Ranking for Product-Related Questions via Multiple Semantic Relations Modeling
Wenxuan Zhang, Yang Deng, Wai Lam
Many E-commerce sites now offer product-specific question answering platforms for users to communicate with each other by posting and answering questions during online shopping. Ho…
Review-guided Helpful Answer Identification in E-commerce
Wenxuan Zhang, Wai Lam, Yang Deng +1
Product-specific community question answering platforms can greatly help address the concerns of potential customers. However, the user-provided answers on such platforms often var…
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
Xin Li, Lidong Bing, Wenxuan Zhang +1
In this paper, we investigate the modeling power of contextualized embeddings from pre-trained language models, e.g. BERT, on the E2E-ABSA task. Specifically, we build a series of…