88 citations · 212 across the 36 of their papers we have counts for
11 papers · 2 filters
DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines
Prakhar Gupta, Yang Liu, Di Jin +6
Dialogue models are able to generate coherent and fluent responses, but they can still be challenging to control and may produce non-engaging, unsafe results. This unpredictability…
Weakly Supervised Data Augmentation Through Prompting for Dialogue Understanding
Maximillian Chen, Alexandros Papangelis, Chenyang Tao +5
Dialogue understanding tasks often necessitate abundant annotated data to achieve good performance and that presents challenges in low-resource settings. To alleviate this barrier,…
UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarization
Yulong Chen, Yang Liu, Ruochen Xu +4
The high annotation costs and diverse demands of various summarization tasks motivate the development of few-shot summarization. However, despite the emergence of many summarizatio…
Alexa, Let's Work Together: Introducing the First Alexa Prize TaskBot Challenge on Conversational Task Assistance
Anna Gottardi, Osman Ipek, Giuseppe Castellucci +27
Since its inception in 2016, the Alexa Prize program has enabled hundreds of university students to explore and compete to develop conversational agents through the SocialBot Grand…
DialogSum Challenge: Results of the Dialogue Summarization Shared Task
Yulong Chen, Naihao Deng, Yang Liu +1
We report the results of DialogSum Challenge, the shared task on summarizing real-life scenario dialogues at INLG 2022. Four teams participate in this shared task and three submit…
A Systematic Evaluation of Response Selection for Open Domain Dialogue
Behnam Hedayatnia, Di Jin, Yang Liu +1
Recent progress on neural approaches for language processing has triggered a resurgence of interest on building intelligent open-domain chatbots. However, even the state-of-the-art…
Improving Bot Response Contradiction Detection via Utterance Rewriting
Di Jin, Sijia Liu, Yang Liu +1
Though chatbots based on large neural models can often produce fluent responses in open domain conversations, one salient error type is contradiction or inconsistency with the prec…
What is wrong with you?: Leveraging User Sentiment for Automatic Dialog Evaluation
Sarik Ghazarian, Behnam Hedayatnia, Alexandros Papangelis +2
Accurate automatic evaluation metrics for open-domain dialogs are in high demand. Existing model-based metrics for system response evaluation are trained on human annotated data, w…
Towards Textual Out-of-Domain Detection without In-Domain Labels
Di Jin, Shuyang Gao, Seokhwan Kim +2
In many real-world settings, machine learning models need to identify user inputs that are out-of-domain (OOD) so as to avoid performing wrong actions. This work focuses on a chall…
Multi-Sentence Knowledge Selection in Open-Domain Dialogue
Mihail Eric, Nicole Chartier, Behnam Hedayatnia +4
Incorporating external knowledge sources effectively in conversations is a longstanding problem in open-domain dialogue research. The existing literature on open-domain knowledge s…
Unsupervised Multi-Granularity Summarization
Ming Zhong, Yang Liu, Suyu Ge +7
Text summarization is a user-preference based task, i.e., for one document, users often have different priorities for summary. As a key aspect of customization in summarization, gr…