1.2k citations · 2k across the 17 of their papers we have counts for
17 papers
Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based Chatbots
Jia-Chen Gu, Zhen-Hua Ling, Quan Liu +2
The challenges of building knowledge-grounded retrieval-based chatbots lie in how to ground a conversation on its background knowledge and how to match response candidates with bot…
DialBERT: A Hierarchical Pre-Trained Model for Conversation Disentanglement
Tianda Li, Jia-Chen Gu, Xiaodan Zhu +4
Disentanglement is a problem in which multiple conversations occur in the same channel simultaneously, and the listener should decide which utterance is part of the conversation he…
Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
Jia-Chen Gu, Tianda Li, Quan Liu +4
In this paper, we study the problem of employing pre-trained language models for multi-turn response selection in retrieval-based chatbots. A new model, named Speaker-Aware BERT (S…
Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language Inference
Tianda Li, Xiaodan Zhu, Quan Liu +3
Natural language inference (NLI) is among the most challenging tasks in natural language understanding. Recent work on unsupervised pretraining that leverages unsupervised signals…
Exploring Unsupervised Pretraining and Sentence Structure Modelling for Winograd Schema Challenge
Yu-Ping Ruan, Xiaodan Zhu, Zhen-Hua Ling +3
Winograd Schema Challenge (WSC) was proposed as an AI-hard problem in testing computers' intelligence on common sense representation and reasoning. This paper presents the new stat…
Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data
Hao Li, Yang Wang, Xinyu Liu +2
We propose a nested recurrent neural network (nested RNN) model for English spelling error correction and generate pseudo data based on phonetic similarity to train it. The model f…