Marius Mosbach

According to our database1, Marius Mosbach authored at least 29 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
What explains the success of cross-modal fine-tuning with ORCA?
CoRR, 2024

The Hidden Space of Transformer Language Adapters.
CoRR, 2024

The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis.
CoRR, 2024

2023
Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures.
CoRR, 2023

Weaker Than You Think: A Critical Look atWeakly Supervised Learning.
CoRR, 2023

Weaker Than You Think: A Critical Look at Weakly Supervised Learning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Fusing Sentence Embeddings Into LSTM-based Autoregressive Language Models.
CoRR, 2022

Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions.
CoRR, 2022

StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypes.
CoRR, 2022

Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages.
CoRR, 2022

Knowledge Base Index Compression via Dimensionality and Precision Reduction.
CoRR, 2022

Artefact Retrieval: Overview of NLP Models with Knowledge Base Access.
CoRR, 2022

MCSE: Multimodal Contrastive Learning of Sentence Embeddings.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021
Graph-based Argument Quality Assessment.
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), 2021

incom.py 2.0 - Calculating Linguistic Distances and Asymmetries in Auditory Perception of Closely Related Languages.
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), 2021

Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical Study.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Fusion Models for Improved Visual Captioning.
CoRR, 2020

Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation.
CoRR, 2020

Fusion Models for Improved Image Captioning.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

On the Security Relevance of Initial Weights in Deep Neural Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

A Closer Look at Linguistic Knowledge in Masked Language Models: The Case of Relative Clauses in American English.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

On the Interplay Between Fine-tuning and Sentence-Level Probing for Linguistic Knowledge in Pre-Trained Transformers.
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020

2019
Adversarial Initialization - when your network performs the way I want.
CoRR, 2019

incom.py - A Toolbox for Calculating Linguistic Distances and Asymmetries between Related Languages.
Proceedings of the International Conference on Recent Advances in Natural Language Processing, 2019

Some steps towards the generation of diachronic WordNets.
Proceedings of the 22nd Nordic Conference on Computational Linguistics, NoDaLiDa 2019, Turku, Finland, September 30, 2019

2018
Logit Pairing Methods Can Fool Gradient-Based Attacks.
CoRR, 2018


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