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cs.CL2025

Mechanistic Decomposition of Sentence Representations

Matthieu Tehenan, Vikram Natarajan, Jonathan Michala +2

Sentence embeddings are central to modern NLP and AI systems, yet little is known about their internal structure. While we can compare these embeddings using measures such as cosin…

cs.CL2024

On the Role of Summary Content Units in Text Summarization Evaluation

Marcel Nawrath, Agnieszka Nowak, Tristan Ratz +13

At the heart of the Pyramid evaluation method for text summarization lie human written summary content units (SCUs). These SCUs are concise sentences that decompose a summary into…

cs.CL2023

The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics

Christoph Leiter, Juri Opitz, Daniel Deutsch +3

With an increasing number of parameters and pre-training data, generative large language models (LLMs) have shown remarkable capabilities to solve tasks with minimal or no task-rel…

cs.CL2023

Gzip versus bag-of-words for text classification

Juri Opitz

The effectiveness of compression in text classification ('gzip') has recently garnered lots of attention. In this note we show that `bag-of-words' approaches can achieve similar or…

cs.CL2023

With a Little Push, NLI Models can Robustly and Efficiently Predict Faithfulness

Julius Steen, Juri Opitz, Anette Frank +1

Conditional language models still generate unfaithful output that is not supported by their input. These unfaithful generations jeopardize trust in real-world applications such as…

cs.CL2023

Similarity-weighted Construction of Contextualized Commonsense Knowledge Graphs for Knowledge-intense Argumentation Tasks

Moritz Plenz, Juri Opitz, Philipp Heinisch +2

Arguments often do not make explicit how a conclusion follows from its premises. To compensate for this lack, we enrich arguments with structured background knowledge to support kn…