Marius Mosbach
21 papers · 2020–2025 · 7 venues · across top CS/AI venues
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Papers
Understanding the Influence of Synthetic Data for Text Embedders
ACL 2025
An Interactive Toolkit for Approachable NLP
ACL 2024
Exploring the Effectiveness and Consistency of Task Selection in Intermediate-Task Transfer Learning
ACL 2024
From Insights to Actions: The Impact of Interpretability and Analysis Research on NLP
EMNLP 2024
Modeling Diachronic Change in English Scientific Writing over 300+ Years with Transformer-based Language Model Surprisal
COLING 2024
The Hidden Space of Transformer Language Adapters
ACL 2024
The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis
ACL 2024
What explains the success of cross-modal fine-tuning with ORCA?
NAACL 2024
Analyzing Pre-trained and Fine-tuned Language Models
EMNLP 2023
Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation
ACL 2023
Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures
CoNLL 2023
Weaker Than You Think: A Critical Look at Weakly Supervised Learning
ACL 2023
Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning
COLING 2022
Knowledge Base Index Compression via Dimensionality and Precision Reduction
ACL 2022
MCSE: Multimodal Contrastive Learning of Sentence Embeddings
NAACL 2022
StereoKG: Data-Driven Knowledge Graph Construction For Cultural Knowledge and Stereotypes
NAACL 2022
Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical Study
Interspeech 2021
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
ICLR 2021
A Closer Look at Linguistic Knowledge in Masked Language Models: The Case of Relative Clauses in American English
COLING 2020
On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers
EMNLP 2020
On the Interplay Between Fine-tuning and Sentence-Level Probing for Linguistic Knowledge in Pre-Trained Transformers
EMNLP 2020