414 citations · 796 across the 11 of their papers we have counts for
11 papers
Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging
Jinglan Gong, Jiefan Lu, Hewei Guo +5
Evaluating large language models (LLMs) as multi-turn conversational partners requires probing capabilities that single-turn benchmarks miss: persona consistency, evolving intent t…
An Empirical Study of Memorization in NLP
Xiaosen Zheng, Jing Jiang
A recent study by Feldman (2020) proposed a long-tail theory to explain the memorization behavior of deep learning models. However, memorization has not been empirically verified i…
Aspect and Opinion Aware Abstractive Review Summarization with Reinforced Hard Typed Decoder
Yufei Tian, Jianfei Yu, Jing Jiang
In this paper, we study abstractive review summarization.Observing that review summaries often consist of aspect words, opinion words and context words, we propose a two-stage rein…
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
Shuohang Wang, Sheng Zhang, Yelong Shen +4
Commonsense reasoning is fundamental to natural language understanding. While traditional methods rely heavily on human-crafted features and knowledge bases, we explore learning co…
Did you take the pill? - Detecting Personal Intake of Medicine from Twitter
Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah +1
Mining social media messages such as tweets, articles, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. S…
Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce
Jianfei Yu, Minghui Qiu, Jing Jiang +4
In this paper, we study transfer learning for the PI and NLI problems, aiming to propose a general framework, which can effectively and efficiently adapt the shared knowledge learn…
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
Shuohang Wang, Mo Yu, Jing Jiang +7
A popular recent approach to answering open-domain questions is to first search for question-related passages and then apply reading comprehension models to extract answers. Existi…
R: Reinforced Reader-Ranker for Open-Domain Question Answering
Shuohang Wang, Mo Yu, Xiaoxiao Guo +7
In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results i…
A Compare-Aggregate Model for Matching Text Sequences
Shuohang Wang, Jing Jiang
Many NLP tasks including machine comprehension, answer selection and text entailment require the comparison between sequences. Matching the important units between sequences is a k…
Machine Comprehension Using Match-LSTM and Answer Pointer
Shuohang Wang, Jing Jiang
Machine comprehension of text is an important problem in natural language processing. A recently released dataset, the Stanford Question Answering Dataset (SQuAD), offers a large n…
Learning Natural Language Inference with LSTM
Shuohang Wang, Jing Jiang
Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Infere…