Maximilian Spliethöver
8 papers · 2019–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (24) 🐣 Hot Topic Early Bird
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The Questioner
(2)
Venues
Top co-authors
Research topics
Machine Learning
(7)
Natural Language Processing
(6)
Application Areas
(6)
Artificial Intelligence
(4)
Core AI
(4)
Deep Learning
(3)
Applications
(3)
Learning Types · Machine Learning
(3)
Core Methods
(2)
Generation
(2)
Interdisciplinary
(1)
Mathematics & Optimization
(1)
Architectures
(1)
Learning Types · Deep Learning
(1)
Linguistics
(1)
Keywords
social bia
(4)
word embedding
(3)
text classification
(2)
social bias detection
(2)
argument mining
(1)
attention mechanism
(1)
multi-task learning
(1)
silhouette analysis
(1)
extractive summarization
(1)
computational argumentation
(1)
bias detection
(1)
siamese neural network
(1)
instruction fine-tuning
(1)
prompt engineering
(1)
bidirectional lstm
(1)
natural language generation
(1)
bias metric
(1)
robustness analysis
(1)
natural language processing
(1)
contrastive learning
(1)
Papers
Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection
NAACL 2025
Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness
ACL 2024
No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media
EMNLP 2022
To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation
EMNLP 2022
Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models
IJCAI 2021
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
EMNLP 2021
Argument from Old Man’s View: Assessing Social Bias in Argumentation
COLING 2020
Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation
ACL 2019