activity
20202023
most citedG-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

88 citations · 212 across the 36 of their papers we have counts for

collaborators
Showing 2022Show all

12 papers · 1 filter

cs.CL2022★ 1 cited

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…

cs.CV2022★ 8 cited

Unifying Vision, Text, and Layout for Universal Document Processing

Zineng Tang, Ziyi Yang, Guoxin Wang +6

We propose Universal Document Processing (UDOP), a foundation Document AI model which unifies text, image, and layout modalities together with varied task formats, including docume…

cs.CL2022★ 7 cited

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,…

cs.CL2022★ 4 cited

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…

cs.CL2022★ 10 cited

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…

cs.CL2022★ 1 cited

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…

cs.CL2022

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…

cs.CL2022★ 1 cited

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…

cs.CL2022★ 3 cited

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…

cs.CL2022

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…

cs.CL2022

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…

cs.CL2022★ 2 cited

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…