2 citations · 3 across the 4 of their papers we have counts for
8 papers
Prompt-driven efficient Open-set Semi-supervised Learning
Haoran Li, Chun-Mei Feng, Tao Zhou +2
Open-set semi-supervised learning (OSSL) has attracted growing interest, which investigates a more practical scenario where out-of-distribution (OOD) samples are only contained in…
You Don't Know My Favorite Color: Preventing Dialogue Representations from Revealing Speakers' Private Personas
Haoran Li, Yangqiu Song, Lixin Fan
Social chatbots, also known as chit-chat chatbots, evolve rapidly with large pretrained language models. Despite the huge progress, privacy concerns have arisen recently: training…
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining
Alexander R. Fabbri, Faiaz Rahman, Imad Rizvi +4
While online conversations can cover a vast amount of information in many different formats, abstractive text summarization has primarily focused on modeling solely news articles.…
Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation
Alexander R. Fabbri, Simeng Han, Haoyuan Li +5
Models pretrained with self-supervised objectives on large text corpora achieve state-of-the-art performance on English text summarization tasks. However, these models are typicall…
Conversational Semantic Parsing
Armen Aghajanyan, Jean Maillard, Akshat Shrivastava +8
The structured representation for semantic parsing in task-oriented assistant systems is geared towards simple understanding of one-turn queries. Due to the limitations of the repr…
MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark
Haoran Li, Abhinav Arora, Shuohui Chen +3
Scaling semantic parsing models for task-oriented dialog systems to new languages is often expensive and time-consuming due to the lack of available datasets. Available datasets su…