667 citations · 1.4k across the 19 of their papers we have counts for
15 papers · 1 filter
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…
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…
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…