616 citations · 931 across the 24 of their papers we have counts for
25 papers
Query Enhanced Knowledge-Intensive Conversation via Unsupervised Joint Modeling
Mingzhu Cai, Siqi Bao, Xin Tian +3
In this paper, we propose an unsupervised query enhanced approach for knowledge-intensive conversations, namely QKConv. There are three modules in QKConv: a query generator, an off…
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…
Q-TOD: A Query-driven Task-oriented Dialogue System
Xin Tian, Yingzhan Lin, Mengfei Song +5
Existing pipelined task-oriented dialogue systems usually have difficulties adapting to unseen domains, whereas end-to-end systems are plagued by large-scale knowledge bases in pra…
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…
GEM-2: Next Generation Molecular Property Prediction Network by Modeling Full-range Many-body Interactions
Lihang Liu, Donglong He, Xiaomin Fang +4
Molecular property prediction is a fundamental task in the drug and material industries. Physically, the properties of a molecule are determined by its own electronic structure, wh…
HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle
Guoxia Wang, Xiaomin Fang, Zhihua Wu +6
Accurate protein structure prediction can significantly accelerate the development of life science. The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, i…
HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative
Xiaomin Fang, Fan Wang, Lihang Liu +7
AI-based protein structure prediction pipelines, such as AlphaFold2, have achieved near-experimental accuracy. These advanced pipelines mainly rely on Multiple Sequence Alignments…
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…
HelixADMET: a robust and endpoint extensible ADMET system incorporating self-supervised knowledge transfer
Shanzhuo Zhang, Zhiyuan Yan, Yueyang Huang +8
Accurate ADMET (an abbreviation for "absorption, distribution, metabolism, excretion, and toxicity") predictions can efficiently screen out undesirable drug candidates in the early…
TOD-DA: Towards Boosting the Robustness of Task-oriented Dialogue Modeling on Spoken Conversations
Xin Tian, Xinxian Huang, Dongfeng He +11
Task-oriented dialogue systems have been plagued by the difficulties of obtaining large-scale and high-quality annotated conversations. Furthermore, most of the publicly available…
Docking-based Virtual Screening with Multi-Task Learning
Zijing Liu, Xianbin Ye, Xiaomin Fang +3
Machine learning shows great potential in virtual screening for drug discovery. Current efforts on accelerating docking-based virtual screening do not consider using existing data…
Multimodal Pre-Training Model for Sequence-based Prediction of Protein-Protein Interaction
Yang Xue, Zijing Liu, Xiaomin Fang +1
Protein-protein interactions (PPIs) are essentials for many biological processes where two or more proteins physically bind together to achieve their functions. Modeling PPIs is us…
HelixMO: Sample-Efficient Molecular Optimization in Scene-Sensitive Latent Space
Zhiyuan Chen, Xiaomin Fang, Zixu Hua +3
Efficient exploration of the chemical space to search the candidate drugs that satisfy various constraints is a fundamental task of drug discovery. Advanced deep generative methods…
Amendable Generation for Dialogue State Tracking
Xin Tian, Liankai Huang, Yingzhan Lin +6
In task-oriented dialogue systems, recent dialogue state tracking methods tend to perform one-pass generation of the dialogue state based on the previous dialogue state. The mistak…
PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation
Siqi Bao, Huang He, Fan Wang +11
To explore the limit of dialogue generation pre-training, we present the models of PLATO-XL with up to 11 billion parameters, trained on both Chinese and English social media conve…
Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning
Fan Wang, Hao Tian, Haoyi Xiong +5
Artificial neural networks (ANNs) are typically confined to accomplishing pre-defined tasks by learning a set of static parameters. In contrast, biological neural networks (BNNs) c…
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction
Xiaomin Fang, Lihang Liu, Jieqiong Lei +6
Effective molecular representation learning is of great importance to facilitate molecular property prediction, which is a fundamental task for the drug and material industry. Rece…
A Unified Pre-training Framework for Conversational AI
Siqi Bao, Bingjin Chen, Huang He +7
In this work, we explore the application of PLATO-2 on various dialogue systems, including open-domain conversation, knowledge grounded dialogue, and task-oriented conversation. PL…
Learning to Select External Knowledge with Multi-Scale Negative Sampling
Huang He, Hua Lu, Siqi Bao +4
The Track-1 of DSTC9 aims to effectively answer user requests or questions during task-oriented dialogues, which are out of the scope of APIs/DB. By leveraging external knowledge r…
Proactive Interaction Framework for Intelligent Social Receptionist Robots
Yang Xue, Fan Wang, Hao Tian +4
Proactive human-robot interaction (HRI) allows the receptionist robots to actively greet people and offer services based on vision, which has been found to improve acceptability an…
PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning
Siqi Bao, Huang He, Fan Wang +6
To build a high-quality open-domain chatbot, we introduce the effective training process of PLATO-2 via curriculum learning. There are two stages involved in the learning process.…
PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable
Siqi Bao, Huang He, Fan Wang +2
Pre-training models have been proved effective for a wide range of natural language processing tasks. Inspired by this, we propose a novel dialogue generation pre-training framewor…
Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection
Chaotao Chen, Jinhua Peng, Fan Wang +2
In human conversation an input post is open to multiple potential responses, which is typically regarded as a one-to-many problem. Promising approaches mainly incorporate multiple…
Know More about Each Other: Evolving Dialogue Strategy via Compound Assessment
Siqi Bao, Huang He, Fan Wang +2
In this paper, a novel Generation-Evaluation framework is developed for multi-turn conversations with the objective of letting both participants know more about each other. For the…