38 citations · 84 across the 4 of their papers we have counts for
7 papers · 1 filter
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…
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…
Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling +3
The RepEval 2017 Shared Task aims to evaluate natural language understanding models for sentence representation, in which a sentence is represented as a fixed-length vector with ne…