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Patrick Huber

14 papers hereh-index 10215 citations24 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author10
  • middle author4

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CL14
same name
  • Patrick Huber — 21 papers
  • Patrick Huber — 9 papers, h 4
  • Patrick Huber — 8 papers, h 5
  • Patrick Huber — 7 papers
  • Patrick Huber — 5 papers, h 7
  • Patrick Huber — 5 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182022
most citedImproving Topic Segmentation by Injecting Discourse Dependencies

2 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

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★ 2 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…

cs.CL2022★ 1 cited

Towards Understanding Large-Scale Discourse Structures in Pre-Trained and Fine-Tuned Language Models

Patrick Huber, Giuseppe Carenini

With a growing number of BERTology work analyzing different components of pre-trained language models, we extend this line of research through an in-depth analysis of discourse inf…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.