667 citations · 1.4k across the 19 of their papers we have counts for
19 papers
CharacterChat: Learning towards Conversational AI with Personalized Social Support
Quan Tu, Chuanqi Chen, Jinpeng Li +5
In our modern, fast-paced, and interconnected world, the importance of mental well-being has grown into a matter of great urgency. However, traditional methods such as Emotional Su…
Assisting Language Learners: Automated Trans-Lingual Definition Generation via Contrastive Prompt Learning
Hengyuan Zhang, Dawei Li, Yanran Li +3
The standard definition generation task requires to automatically produce mono-lingual definitions (e.g., English definitions for English words), but ignores that the generated def…
Distinguishability Calibration to In-Context Learning
Hongjing Li, Hanqi Yan, Yanran Li +3
Recent years have witnessed increasing interests in prompt-based learning in which models can be trained on only a few annotated instances, making them suitable in low-resource set…
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation
Xiangyu Qin, Zhiyu Wu, Jinshi Cui +5
Previous works on emotion recognition in conversation (ERC) follow a two-step paradigm, which can be summarized as first producing context-independent features via fine-tuning pret…
Fine-grained Contrastive Learning for Definition Generation
Hengyuan Zhang, Dawei Li, Shiping Yang +1
Recently, pre-trained transformer-based models have achieved great success in the task of definition generation (DG). However, previous encoder-decoder models lack effective repres…
C3KG: A Chinese Commonsense Conversation Knowledge Graph
Dawei Li, Yanran Li, Jiayi Zhang +4
Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational models to plan the next steps. To fill the gap,…
MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation
Quan Tu, Yanran Li, Jianwei Cui +3
Applying existing methods to emotional support conversation -- which provides valuable assistance to people who are in need -- has two major limitations: (a) they generally employ…
Towards an Online Empathetic Chatbot with Emotion Causes
Yanran Li, Ke Li, Hongke Ning +5
Existing emotion-aware conversational models usually focus on controlling the response contents to align with a specific emotion class, whereas empathy is the ability to understand…
Writing Polishment with Simile: Task, Dataset and A Neural Approach
Jiayi Zhang, Zhi Cui, Xiaoqiang Xia +4
A simile is a figure of speech that directly makes a comparison, showing similarities between two different things, e.g. "Reading papers can be dull sometimes,like watching grass g…
Focus-Constrained Attention Mechanism for CVAE-based Response Generation
Zhi Cui, Yanran Li, Jiayi Zhang +3
To model diverse responses for a given post, one promising way is to introduce a latent variable into Seq2Seq models. The latent variable is supposed to capture the discourse-level…
PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting
Shuo Wang, Yanran Li, Jiang Zhang +3
When predicting PM2.5 concentrations, it is necessary to consider complex information sources since the concentrations are influenced by various factors within a long period. In th…
Incorporating Relevant Knowledge in Context Modeling and Response Generation
Yanran Li, Wenjie Li, Ziqiang Cao +1
To sustain engaging conversation, it is critical for chatbots to make good use of relevant knowledge. Equipped with a knowledge base, chatbots are able to extract conversation-rela…
Meta-path Augmented Response Generation
Yanran Li, Wenjie Li
We propose a chatbot, namely Mocha to make good use of relevant entities when generating responses. Augmented with meta-path information, Mocha is able to mention proper entities f…
DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
Yanran Li, Hui Su, Xiaoyu Shen +3
We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset…
A Conditional Variational Framework for Dialog Generation
Xiaoyu Shen, Hui Su, Yanran Li +5
Deep latent variable models have been shown to facilitate the response generation for open-domain dialog systems. However, these latent variables are highly randomized, leading to…
Maximum-Likelihood Augmented Discrete Generative Adversarial Networks
Tong Che, Yanran Li, Ruixiang Zhang +4
Despite the successes in capturing continuous distributions, the application of generative adversarial networks (GANs) to discrete settings, like natural language tasks, is rather…
Mode Regularized Generative Adversarial Networks
Tong Che, Yanran Li, Athul Paul Jacob +2
Although Generative Adversarial Networks achieve state-of-the-art results on a variety of generative tasks, they are regarded as highly unstable and prone to miss modes. We argue t…
AttSum: Joint Learning of Focusing and Summarization with Neural Attention
Ziqiang Cao, Wenjie Li, Sujian Li +2
Query relevance ranking and sentence saliency ranking are the two main tasks in extractive query-focused summarization. Previous supervised summarization systems often perform the…
Component-Enhanced Chinese Character Embeddings
Yanran Li, Wenjie Li, Fei Sun +1
Distributed word representations are very useful for capturing semantic information and have been successfully applied in a variety of NLP tasks, especially on English. In this wor…