activity
20192023
most citedSystematically Exploring Redundancy Reduction in Summarizing Long Documents

15 citations · 34 across the 22 of their papers we have counts for

collaborators

27 papers

cs.CL2023

Tracing Influence at Scale: A Contrastive Learning Approach to Linking Public Comments and Regulator Responses

Linzi Xing, Brad Hackinen, Giuseppe Carenini

U.S. Federal Regulators receive over one million comment letters each year from businesses, interest groups, and members of the public, all advocating for changes to proposed regul…

cs.CL2023

Visual Analytics for Generative Transformer Models

Raymond Li, Ruixin Yang, Wen Xiao +3

While transformer-based models have achieved state-of-the-art results in a variety of classification and generation tasks, their black-box nature makes them challenging for interpr…

cs.CL2022

Towards Domain-Independent Supervised Discourse Parsing Through Gradient Boosting

Patrick Huber, Giuseppe Carenini

Discourse analysis and discourse parsing have shown great impact on many important problems in the field of Natural Language Processing (NLP). Given the direct impact of discourse…

cs.CL2022

Unsupervised Inference of Data-Driven Discourse Structures using a Tree Auto-Encoder

Patrick Huber, Giuseppe Carenini

With a growing need for robust and general discourse structures in many downstream tasks and real-world applications, the current lack of high-quality, high-quantity discourse tree…

cs.CL2022

Transition to Adulthood for Young People with Intellectual or Developmental Disabilities: Emotion Detection and Topic Modeling

Yan Liu, Maria Laricheva, Chiyu Zhang +5

Transition to Adulthood is an essential life stage for many families. The prior research has shown that young people with intellectual or development disabil-ities (IDD) have more…

cs.CL20222 cited

Improving Topic Segmentation by Injecting Discourse Dependencies

Linzi Xing, Patrick Huber, Giuseppe Carenini

Recent neural supervised topic segmentation models achieve distinguished superior effectiveness over unsupervised methods, with the availability of large-scale training corpora sam…