3 citations · 3 across the 5 of their papers we have counts for
5 papers
Variation is the Norm: Embracing Sociolinguistics in NLP
Anne-Marie Lutgen, Alistair Plum, Verena Blaschke +2
In Natural Language Processing (NLP), variation is typically seen as noise and "normalised away" before processing, even though it is an integral part of language. Conversely, stud…
From Noise to Signal to Selbstzweck: Reframing Human Label Variation in the Era of Post-training in NLP
Shanshan Xu, Santosh T. Y. S. S, Barbara Plank
Human Label Variation (HLV) refers to legitimate disagreement in annotation that reflects the diversity of human perspectives rather than mere error. Long treated in NLP as noise t…
Better Aligned with Survey Respondents or Training Data? Unveiling Political Leanings of LLMs on U.S. Supreme Court Cases
Shanshan Xu, T. Y. S. S Santosh, Yanai Elazar +3
Recent works have shown that Large Language Models (LLMs) have a tendency to memorize patterns and biases present in their training data, raising important questions about how such…
Through the Lens of Split Vote: Exploring Disagreement, Difficulty and Calibration in Legal Case Outcome Classification
Shanshan Xu, T. Y. S. S Santosh, Oana Ichim +2
In legal decisions, split votes (SV) occur when judges cannot reach a unanimous decision, posing a difficulty for lawyers who must navigate diverse legal arguments and opinions. In…
From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification
Shanshan Xu, T. Y. S. S Santosh, Oana Ichim +3
In legal NLP, Case Outcome Classification (COC) must not only be accurate but also trustworthy and explainable. Existing work in explainable COC has been limited to annotations by…