Michael A. Hedderich

Orcid: 0000-0001-6858-0791

According to our database1, Michael A. Hedderich authored at least 26 papers between 2018 and 2024.

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

Timeline

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Bibliography

2024
The Potential and Challenges of Evaluating Attitudes, Opinions, and Values in Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

A Piece of Theatre: Investigating How Teachers Design LLM Chatbots to Assist Adolescent Cyberbullying Education.
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

Understanding Human-AI Workflows for Generating Personas.
Proceedings of the Designing Interactive Systems Conference, 2024

2023
SparseIMU: Computational Design of Sparse IMU Layouts for Sensing Fine-grained Finger Microgestures.
ACM Trans. Comput. Hum. Interact., 2023

Understanding and Mitigating Classification Errors Through Interpretable Token Patterns.
CoRR, 2023

Meta Self-Refinement for Robust Learning with Weak Supervision.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2022
Weak supervision and label noise handling for Natural language processing in low-resource scenarios.
PhD thesis, 2022

Task-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A Study on Text Classification for African Languages.
CoRR, 2022

Chatbots Facilitating Consensus-Building in Asynchronous Co-Design.
Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, 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

Label-Descriptive Patterns and Their Application to Characterizing Classification Errors.
Proceedings of the International Conference on Machine Learning, 2022

Is BERT Robust to Label Noise? A Study on Learning with Noisy Labels in Text Classification.
Proceedings of the Third Workshop on Insights from Negative Results in NLP, 2022

2021
Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL).
CoRR, 2021

ANEA: Distant Supervision for Low-Resource Named Entity Recognition.
CoRR, 2021

A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Estimating Formulas for Model Performance Under Noisy Labels Using Symbolic Regression.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

SoloFinger: Robust Microgestures while Grasping Everyday Objects.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Analysing the Noise Model Error for Realistic Noisy Label Data.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Functions to Study the Benefit of Multitask Learning.
CoRR, 2020

Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yorùbá.
Proceedings of the 1st AfricaNLP Workshop Proceedings, 2020

Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 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
Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Using Multi-Sense Vector Embeddings for Reverse Dictionaries.
Proceedings of the 13th International Conference on Computational Semantics, 2019

Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018
Training a Neural Network in a Low-Resource Setting on Automatically Annotated Noisy Data.
Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP, 2018


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