40 citations · 87 across the 9 of their papers we have counts for
9 papers
Dialogue Language Model with Large-Scale Persona Data Engineering
Mengze Hong, Chen Jason Zhang, Chaotao Chen +2
Maintaining persona consistency is paramount in the application of open-domain dialogue systems, as exemplified by models like ChatGPT. Despite significant advancements, the limite…
Acoustic Model Optimization over Multiple Data Sources: Merging and Valuation
Victor Junqiu Wei, Weicheng Wang, Di Jiang +2
Due to the rising awareness of privacy protection and the voluminous scale of speech data, it is becoming infeasible for Automatic Speech Recognition (ASR) system developers to tra…
DAL: Dual Adversarial Learning for Dialogue Generation
Shaobo Cui, Rongzhong Lian, Di Jiang +3
In open-domain dialogue systems, generative approaches have attracted much attention for response generation. However, existing methods are heavily plagued by generating safe respo…
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…
Proactive Human-Machine Conversation with Explicit Conversation Goals
Wenquan Wu, Zhen Guo, Xiangyang Zhou +4
Though great progress has been made for human-machine conversation, current dialogue system is still in its infancy: it usually converses passively and utters words more as a matte…
Artificial Intelligence for Prosthetics - challenge solutions
Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty +47
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a giv…
Learning to Select Knowledge for Response Generation in Dialog Systems
Rongzhong Lian, Min Xie, Fan Wang +2
End-to-end neural models for intelligent dialogue systems suffer from the problem of generating uninformative responses. Various methods were proposed to generate more informative…
Familia: A Configurable Topic Modeling Framework for Industrial Text Engineering
Di Jiang, Yuanfeng Song, Rongzhong Lian +4
In the last decade, a variety of topic models have been proposed for text engineering. However, except Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation…
Familia: An Open-Source Toolkit for Industrial Topic Modeling
Di Jiang, Zeyu Chen, Rongzhong Lian +2
Familia is an open-source toolkit for pragmatic topic modeling in industry. Familia abstracts the utilities of topic modeling in industry as two paradigms: semantic representation…