158 citations · 593 across the 50 of their papers we have counts for
11 papers · 1 filter
Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization
Artidoro Pagnoni, Alexander R. Fabbri, Wojciech Kryściński +1
In long document controllable summarization, where labeled data is scarce, pretrained models struggle to adapt to the task and effectively respond to user queries. In this paper, w…
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation
Yixin Liu, Alexander R. Fabbri, Pengfei Liu +8
Human evaluation is the foundation upon which the evaluation of both summarization systems and automatic metrics rests. However, existing human evaluation studies for summarization…
Improving Factual Consistency in Summarization with Compression-Based Post-Editing
Alexander R. Fabbri, Prafulla Kumar Choubey, Jesse Vig +2
State-of-the-art summarization models still struggle to be factually consistent with the input text. A model-agnostic way to address this problem is post-editing the generated summ…
Discord Questions: A Computational Approach To Diversity Analysis in News Coverage
Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs'ka +2
There are many potential benefits to news readers accessing diverse sources. Modern news aggregators do the hard work of organizing the news, offering readers a plethora of source…
Conformal Predictor for Improving Zero-shot Text Classification Efficiency
Prafulla Kumar Choubey, Yu Bai, Chien-Sheng Wu +2
Pre-trained language models (PLMs) have been shown effective for zero-shot (0shot) text classification. 0shot models based on natural language inference (NLI) and next sentence pre…
Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning
Xiangyu Peng, Chen Xing, Prafulla Kumar Choubey +2
Prompt tuning approaches, which learn task-specific soft prompts for a downstream task conditioning on frozen pre-trained models, have attracted growing interest due to its paramet…
Marvista: Exploring the Design of a Human-AI Collaborative News Reading Tool
Xiang 'Anthony' Chen, Chien-Sheng Wu, Lidiya Murakhovs'ka +4
We explore the design of Marvista -- a human-AI collaborative tool that employs a suite of natural language processing models to provide end-to-end support for reading online news…
Quiz Design Task: Helping Teachers Create Quizzes with Automated Question Generation
Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs'ka +2
Question generation (QGen) models are often evaluated with standardized NLG metrics that are based on n-gram overlap. In this paper, we measure whether these metric improvements tr…
Near-Negative Distinction: Giving a Second Life to Human Evaluation Datasets
Philippe Laban, Chien-Sheng Wu, Wenhao Liu +1
Precisely assessing the progress in natural language generation (NLG) tasks is challenging, and human evaluation to establish a preference in a model's output over another is often…
Structure Extraction in Task-Oriented Dialogues with Slot Clustering
Liang Qiu, Chien-Sheng Wu, Wenhao Liu +1
Extracting structure information from dialogue data can help us better understand user and system behaviors. In task-oriented dialogues, dialogue structure has often been considere…
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
Tianbao Xie, Chen Henry Wu, Peng Shi +20
Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases and question answering over knowledge bases.…