8 citations · 18 across the 11 of their papers we have counts for
11 papers
SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering
Yuqing Fu, Yimin Deng, Wanyu Wang +9
Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reasoning paths in response to th…
Prompt Pool based Class-Incremental Continual Learning for Dialog State Tracking
Hong Liu, Yucheng Cai, Yuan Zhou +3
Continual learning is crucial for dialog state tracking (DST) in dialog systems, since requirements from users for new functionalities are often encountered. However, most of exist…
Exploring Energy-based Language Models with Different Architectures and Training Methods for Speech Recognition
Hong Liu, Zhaobiao Lv, Zhijian Ou +2
Energy-based language models (ELMs) parameterize an unnormalized distribution for natural sentences and are radically different from popular autoregressive language models (ALMs).…
Knowledge-Retrieval Task-Oriented Dialog Systems with Semi-Supervision
Yucheng Cai, Hong Liu, Zhijian Ou +2
Most existing task-oriented dialog (TOD) systems track dialog states in terms of slots and values and use them to query a database to get relevant knowledge to generate responses.…
A Generative User Simulator with GPT-based Architecture and Goal State Tracking for Reinforced Multi-Domain Dialog Systems
Hong Liu, Yucheng Cai, Zhijian Ou +2
Building user simulators (USs) for reinforcement learning (RL) of task-oriented dialog systems (DSs) has gained more and more attention, which, however, still faces several fundame…
Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset
Hong Liu, Hao Peng, Zhijian Ou +3
Recently, there have merged a class of task-oriented dialogue (TOD) datasets collected through Wizard-of-Oz simulated games. However, the Wizard-of-Oz data are in fact simulated da…
Advancing Semi-Supervised Task Oriented Dialog Systems by JSA Learning of Discrete Latent Variable Models
Yucheng Cai, Hong Liu, Zhijian Ou +2
Developing semi-supervised task-oriented dialog (TOD) systems by leveraging unlabeled dialog data has attracted increasing interests. For semi-supervised learning of latent state T…
A Challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems
Zhijian Ou, Junlan Feng, Juanzi Li +5
A challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems, Co-located with EMNLP2022 SereTOD Workshop.
Building Markovian Generative Architectures over Pretrained LM Backbones for Efficient Task-Oriented Dialog Systems
Hong Liu, Yucheng Cai, Zhijian Ou +2
Recently, Transformer based pretrained language models (PLMs), such as GPT2 and T5, have been leveraged to build generative task-oriented dialog (TOD) systems. A drawback of existi…
Variational Latent-State GPT for Semi-Supervised Task-Oriented Dialog Systems
Hong Liu, Yucheng Cai, Zhenru Lin +3
Recently, two approaches, fine-tuning large pre-trained language models and variational training, have attracted significant interests, separately, for semi-supervised end-to-end t…
Elastic CRFs for Open-ontology Slot Filling
Yinpei Dai, Yichi Zhang, Hong Liu +3
Slot filling is a crucial component in task-oriented dialog systems that is used to parse (user) utterances into semantic concepts called slots. An ontology is defined by the colle…