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Isabelle Augenstein

12 papers hereh-index 448 citations10 works total

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

author position
  • middle author1
  • last author7

Across the 8 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CL11
  • cs.CV1
same name
  • Isabelle Augenstein — 112 papers, h 43
  • Isabelle Augenstein — 12 papers, h 7
  • Isabelle Augenstein — 7 papers, h 2
  • Isabelle Augenstein — 6 papers, h 3
  • Isabelle Augenstein — 4 papers, h 2
  • Isabelle Augenstein — 2 papers

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
20242026
collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CL2025

Multi-Step Knowledge Interaction Analysis via Rank-2 Subspace Disentanglement

Sekh Mainul Islam, Pepa Atanasova, Isabelle Augenstein

Natural Language Explanations (NLEs) describe how Large Language Models (LLMs) make decisions by drawing on external Context Knowledge (CK) and Parametric Knowledge (PK). Understan…

cs.CL2025

Evaluation Framework for Highlight Explanations of Context Utilisation in Language Models

Jingyi Sun, Pepa Atanasova, Sagnik Ray Choudhury +2

Context utilisation, the ability of Language Models (LMs) to incorporate relevant information from the provided context when generating responses, remains largely opaque to users,…

cs.CL2025

CUB: Benchmarking Context Utilisation Techniques for Language Models

Lovisa Hagström, Youna Kim, Haeun Yu +4

Incorporating external knowledge is crucial for knowledge-intensive tasks, such as question answering and fact checking. However, language models (LMs) may ignore relevant informat…

cs.CV2025

With Great Backbones Comes Great Adversarial Transferability

Erik Arakelyan, Karen Hambardzumyan, Davit Papikyan +4

Advances in self-supervised learning (SSL) for machine vision have improved representation robustness and model performance, giving rise to pre-trained backbones like \emph{ResNet}…

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