92 citations · 208 across the 9 of their papers we have counts for
10 papers · 1 filter
KETOD: Knowledge-Enriched Task-Oriented Dialogue
Zhiyu Chen, Bing Liu, Seungwhan Moon +3
Existing studies in dialogue system research mostly treat task-oriented dialogue and chit-chat as separate domains. Towards building a human-like assistant that can converse natura…
User Memory Reasoning for Conversational Recommendation
Hu Xu, Seungwhan Moon, Honglei Liu +3
We study a conversational recommendation model which dynamically manages users' past (offline) preferences and current (online) requests through a structured and cumulative user me…
Analyzing the Forgetting Problem in the Pretrain-Finetuning of Dialogue Response Models
Tianxing He, Jun Liu, Kyunghyun Cho +4
In this work, we study how the finetuning stage in the pretrain-finetune framework changes the behavior of a pretrained neural language generator. We focus on the transformer encod…
Adversarial Learning of Task-Oriented Neural Dialog Models
Bing Liu, Ian Lane
In this work, we propose an adversarial learning method for reward estimation in reinforcement learning (RL) based task-oriented dialog models. Most of the current RL based task-or…
Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems
Bing Liu, Gokhan Tur, Dilek Hakkani-Tur +2
In this work, we present a hybrid learning method for training task-oriented dialogue systems through online user interactions. Popular methods for learning task-oriented dialogues…
Multi-Domain Adversarial Learning for Slot Filling in Spoken Language Understanding
Bing Liu, Ian Lane
The goal of this paper is to learn cross-domain representations for slot filling task in spoken language understanding (SLU). Most of the recently published SLU models are domain-s…