6 papers
Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive
Tharindu Cyril Weerasooriya, Sujan Dutta, Tharindu Ranasinghe +3
Offensive speech detection is a key component of content moderation. However, what is offensive can be highly subjective. This paper investigates how machine and human moderators d…
ProRefine: Inference-Time Prompt Refinement with Textual Feedback
Deepak Pandita, Tharindu Cyril Weerasooriya, Ankit Parag Shah +3
Agentic workflows, where multiple AI agents collaborate to accomplish complex tasks like reasoning or planning, play a substantial role in many cutting-edge commercial applications…
Hope vs. Hate: Understanding User Interactions with LGBTQ+ News Content in Mainstream US News Media through the Lens of Hope Speech
Jonathan Pofcher, Christopher M. Homan, Randall Sell +1
This paper makes three contributions. First, via a substantial corpus of 1,419,047 comments posted on 3,161 YouTube news videos of major US cable news outlets, we analyze how users…
LPI-RIT at LeWiDi-2025: Improving Distributional Predictions via Metadata and Loss Reweighting with DisCo
Mandira Sawkar, Samay U. Shetty, Deepak Pandita +2
The Learning With Disagreements (LeWiDi) 2025 shared task aims to model annotator disagreement through soft label distribution prediction and perspectivist evaluation, which focuse…
Subasa - Adapting Language Models for Low-resourced Offensive Language Detection in Sinhala
Shanilka Haturusinghe, Tharindu Cyril Weerasooriya, Marcos Zampieri +2
Accurate detection of offensive language is essential for a number of applications related to social media safety. There is a sharp contrast in performance in this task between low…
Rater Cohesion and Quality from a Vicarious Perspective
Deepak Pandita, Tharindu Cyril Weerasooriya, Sujan Dutta +5
Human feedback is essential for building human-centered AI systems across domains where disagreement is prevalent, such as AI safety, content moderation, or sentiment analysis. Man…