402 citations · 1.1k across the 59 of their papers we have counts for
7 papers · 2 filters
Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling
Yang Deng, Yaliang Li, Wenxuan Zhang +2
Recently, Product Question Answering (PQA) on E-Commerce platforms has attracted increasing attention as it can act as an intelligent online shopping assistant and improve the cust…
HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression
Chenhe Dong, Yaliang Li, Ying Shen +1
On many natural language processing tasks, large pre-trained language models (PLMs) have shown overwhelming performances compared with traditional neural network methods. Neverthel…
Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation
Yuexiang Xie, Fei Sun, Yang Deng +2
Despite significant progress has been achieved in text summarization, factual inconsistency in generated summaries still severely limits its practical applications. Among the key f…
Differential Privacy for Text Analytics via Natural Text Sanitization
Xiang Yue, Minxin Du, Tianhao Wang +3
Texts convey sophisticated knowledge. However, texts also convey sensitive information. Despite the success of general-purpose language models and domain-specific mechanisms with d…
Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge
Yang Deng, Yuexiang Xie, Yaliang Li +3
Answer selection, which is involved in many natural language processing applications such as dialog systems and question answering (QA), is an important yet challenging task in pra…
CRSLab: An Open-Source Toolkit for Building Conversational Recommender System
Kun Zhou, Xiaolei Wang, Yuanhang Zhou +5
In recent years, conversational recommender system (CRS) has received much attention in the research community. However, existing studies on CRS vary in scenarios, goals and techni…
Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation
Lingyun Feng, Minghui Qiu, Yaliang Li +2
Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be…