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Scott Friedman

3 accepted papers

2024

Debiasing Multi-Entity Aspect-Based Sentiment Analysis with Norm-Based Data Augmentation

COLING 2024main

Bias in NLP models may arise from using pre-trained transformer models trained on biased corpora, or by training or fine-tuning directly on corpora with systemic biases. Recent research has explored strategies for reduce measurable biases in NLP predictions while maintaining prediction accuracy on h…

Cited by 1SourcePDFScholar
2024

Recognizing Value Resonance with Resonance-Tuned RoBERTa Task Definition, Experimental Validation, and Robust Modeling

COLING 2024main

Understanding the implicit values and beliefs of diverse groups and cultures using qualitative texts – such as long-form narratives – and domain-expert interviews is a fundamental goal of social anthropology. This paper builds upon a 2022 study that introduced the NLP task of Recognizing Value Reson…

Cited by 2SourcePDFScholar
2021

Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based Results

EMNLP 2021main

Recent transformer-based approaches demonstrate promising results on relational scientific information extraction. Existing datasets focus on high-level description of how research is carried out. Instead we focus on the subtleties of how experimental associations are presented by building SciClaim,…