616 citations · 1.8k across the 64 of their papers we have counts for
12 papers · 2 filters
PLATO-K: Internal and External Knowledge Enhanced Dialogue Generation
Siqi Bao, Huang He, Jun Xu +7
Recently, the practical deployment of open-domain dialogue systems has been plagued by the knowledge issue of information deficiency and factual inaccuracy. To this end, we introdu…
Towards Boosting the Open-Domain Chatbot with Human Feedback
Hua Lu, Siqi Bao, Huang He +3
Many open-domain dialogue models pre-trained with social media comments can generate coherent replies but have difficulties producing engaging responses when interacting with real…
Bi-SimCut: A Simple Strategy for Boosting Neural Machine Translation
Pengzhi Gao, Zhongjun He, Hua Wu +1
We introduce Bi-SimCut: a simple but effective training strategy to boost neural machine translation (NMT) performance. It consists of two procedures: bidirectional pretraining and…
Link the World: Improving Open-domain Conversation with Dynamic Spatiotemporal-aware Knowledge
Han Zhou, Xinchao Xu, Wenquan Wu +5
Making chatbots world aware in a conversation like a human is a crucial challenge, where the world may contain dynamic knowledge and spatiotemporal state. Several recent advances h…
ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrieval
Yuxiang Lu, Yiding Liu, Jiaxiang Liu +8
Neural retrievers based on pre-trained language models (PLMs), such as dual-encoders, have achieved promising performance on the task of open-domain question answering (QA). Their…
Less Learn Shortcut: Analyzing and Mitigating Learning of Spurious Feature-Label Correlation
Yanrui Du, Jing Yan, Yan Chen +6
Recent research has revealed that deep neural networks often take dataset biases as a shortcut to make decisions rather than understand tasks, leading to failures in real-world app…
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP
Lijie Wang, Yaozong Shen, Shuyuan Peng +7
While there is increasing concern about the interpretability of neural models, the evaluation of interpretability remains an open problem, due to the lack of proper evaluation data…
Towards Multi-Turn Empathetic Dialogs with Positive Emotion Elicitation
Shihang Wang, Xinchao Xu, Wenquan Wu +3
Emotional support is a crucial skill for many real-world scenarios, including caring for the elderly, mental health support, and customer service chats. This paper presents a novel…
Where to Go for the Holidays: Towards Mixed-Type Dialogs for Clarification of User Goals
Zeming Liu, Jun Xu, Zeyang Lei +3
Most dialog systems posit that users have figured out clear and specific goals before starting an interaction. For example, users have determined the departure, the destination, an…
A Thorough Examination on Zero-shot Dense Retrieval
Ruiyang Ren, Yingqi Qu, Jing Liu +6
Recent years have witnessed the significant advance in dense retrieval (DR) based on powerful pre-trained language models (PLM). DR models have achieved excellent performance in se…
Long Time No See! Open-Domain Conversation with Long-Term Persona Memory
Xinchao Xu, Zhibin Gou, Wenquan Wu +4
Most of the open-domain dialogue models tend to perform poorly in the setting of long-term human-bot conversations. The possible reason is that they lack the capability of understa…
DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine
Yifu Qiu, Hongyu Li, Yingqi Qu +5
In this paper, we present DuReader_retrieval, a large-scale Chinese dataset for passage retrieval. DuReader_retrieval contains more than 90K queries and over 8M unique passages fro…