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cs.CL2025

AI Debate Aids Assessment of Controversial Claims

Salman Rahman, Sheriff Issaka, Ashima Suvarna +11

As AI grows more powerful, it will increasingly shape how we understand the world. But with this influence comes the risk of amplifying misinformation and deepening social divides-…

cs.CL2025

RTTC: Reward-Guided Collaborative Test-Time Compute

J. Pablo Muñoz, Jinjie Yuan

Test-Time Compute (TTC) has emerged as a powerful paradigm for enhancing the performance of Large Language Models (LLMs) at inference, leveraging strategies such as Test-Time Train…

cs.CL2025

ModelCitizens: Representing Community Voices in Online Safety

Ashima Suvarna, Christina Chance, Karolina Naranjo +4

Automatic toxic language detection is critical for creating safe, inclusive online spaces. However, it is a highly subjective task, with perceptions of toxic language shaped by com…

cs.CL2025

Disparities in LLM Reasoning Accuracy and Explanations: A Case Study on African American English

Runtao Zhou, Guangya Wan, Saadia Gabriel +4

Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning tasks, leading to their widespread deployment. However, recent studies have highlighted concerni…

cs.CL2024

How to Train Your Fact Verifier: Knowledge Transfer with Multimodal Open Models

Jaeyoung Lee, Ximing Lu, Jack Hessel +5

Given the growing influx of misinformation across news and social media, there is a critical need for systems that can provide effective real-time verification of news claims. Larg…