71 citations · 270 across the 48 of their papers we have counts for
12 papers · 2 filters
Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation
Zhexin Zhang, Jiale Cheng, Hao Sun +5
Large pretrained language models can easily produce toxic or biased content, which is prohibitive for practical use. In order to detect such toxic generations, existing methods rel…
KPT: Keyword-guided Pre-training for Grounded Dialog Generation
Qi Zhu, Fei Mi, Zheng Zhang +6
Incorporating external knowledge into the response generation process is essential to building more helpful and reliable dialog agents. However, collecting knowledge-grounded conve…
Towards Diverse, Relevant and Coherent Open-Domain Dialogue Generation via Hybrid Latent Variables
Bin Sun, Yitong Li, Fei Mi +3
Conditional variational models, using either continuous or discrete latent variables, are powerful for open-domain dialogue response generation. However, previous works show that c…
MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Moral Discussions
Hao Sun, Zhexin Zhang, Fei Mi +6
Morality in dialogue systems has raised great attention in research recently. A moral dialogue system aligned with users' values could enhance conversation engagement and user conn…
Modeling Complex Dialogue Mappings via Sentence Semantic Segmentation Guided Conditional Variational Auto-Encoder
Bin Sun, Shaoxiong Feng, Yiwei Li +4
Complex dialogue mappings (CDM), including one-to-many and many-to-one mappings, tend to make dialogue models generate incoherent or dull responses, and modeling these mappings rem…
Exploring Effective Information Utilization in Multi-Turn Topic-Driven Conversations
Jiatong Li, Bin He, Fei Mi
Conversations are always related to certain topics. However, it is challenging to fuse dialogue history and topic information from various sources at the same time in current dialo…
Continual Prompt Tuning for Dialog State Tracking
Qi Zhu, Bing Li, Fei Mi +2
A desirable dialog system should be able to continually learn new skills without forgetting old ones, and thereby adapt to new domains or tasks in its life cycle. However, continua…
Compilable Neural Code Generation with Compiler Feedback
Xin Wang, Yasheng Wang, Yao Wan +7
Automatically generating compilable programs with (or without) natural language descriptions has always been a touchstone problem for computational linguistics and automated softwa…
PanGu-Bot: Efficient Generative Dialogue Pre-training from Pre-trained Language Model
Fei Mi, Yitong Li, Yulong Zeng +7
In this paper, we introduce PanGu-Bot, a Chinese pre-trained open-domain dialogue generation model based on a large pre-trained language model (PLM) PANGU-alpha (Zeng et al.,2021).…
Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarks
Jingyan Zhou, Jiawen Deng, Fei Mi +6
The research of open-domain dialog systems has been greatly prospered by neural models trained on large-scale corpora, however, such corpora often introduce various safety problems…
Pan More Gold from the Sand: Refining Open-domain Dialogue Training with Noisy Self-Retrieval Generation
Yihe Wang, Yitong Li, Yasheng Wang +6
Real human conversation data are complicated, heterogeneous, and noisy, from which building open-domain dialogue systems remains a challenging task. In fact, such dialogue data sti…
COLD: A Benchmark for Chinese Offensive Language Detection
Jiawen Deng, Jingyan Zhou, Hao Sun +4
Offensive language detection is increasingly crucial for maintaining a civilized social media platform and deploying pre-trained language models. However, this task in Chinese is s…