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Found 9 papers, 7 papers with code
Test Harder than You Train: Probing with Extrapolation Splits
Previous work on probing word representations for linguistic knowledge has focused on interpolation tasks.
Where Does Linguistic Information Emerge in Neural Language Models? Measuring Gains and Contributions across Layers
Probing studies have extensively explored where in neural language models linguistic information is located.
How to Tune a Multilingual Encoder Model for Germanic Languages: A Study of PEFT, Full Fine-Tuning, and Language Adapters
This paper investigates the optimal use of the multilingual encoder model mDeBERTa for tasks in three Germanic languages -- German, Swedish, and Icelandic -- representing varying levels of presence and likely data quality in mDeBERTas pre-training data.
Train More Parameters But Mind Their Placement: Insights into Language Adaptation with PEFT
Smaller LLMs still face significant challenges even in medium-resourced languages, particularly when it comes to language-specific knowledge -- a problem not easily resolved with machine-translated data.
Properties and Challenges of LLM-Generated Explanations
The properties of the generated explanations are influenced by the pre-training corpus and by the target data used for instruction fine-tuning.
A Hypothesis-Driven Framework for the Analysis of Self-Rationalising Models
The self-rationalising capabilities of LLMs are appealing because the generated explanations can give insights into the plausibility of the predictions.
The Impact of Language Adapters in Cross-Lingual Transfer for NLU
Modular deep learning has been proposed for the efficient adaption of pre-trained models to new tasks, domains and languages.
Natural Language Understanding
Zero-Shot Cross-Lingual Transfer
Classifier Probes May Just Learn from Linear Context Features
Classifiers trained on auxiliary probing tasks are a popular tool to analyze the representations learned by neural sentence encoders such as BERT and ELMo.
Entity Decisions in Neural Language Modelling: Approaches and Problems
We explore different approaches to explicit entity modelling in language models (LM).
