1 citations · 1 across the 7 of their papers we have counts for
8 papers
CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees
S M Rafiuddin, Atriya Sen
Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…
Jagged Judges: Epistemic Stability Under Perturbation, Pressure, and Persistence
Justin Zhao, Himaghna Bhattacharjee, Hannah Korevaar +2
LLM judges have become central infrastructure for model evaluations, online grading, and reward modeling. Judges are typically validated by accuracy on golden data, but accuracy sa…
ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition
Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2
We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
Gradient-based Jailbreak Images for Multimodal Fusion Models
Javier Rando, Hannah Korevaar, Erik Brinkman +2
Augmenting language models with image inputs may enable more effective jailbreak attacks through continuous optimization, unlike text inputs that require discrete optimization. How…
The Llama 3 Herd of Models
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…
Matched Pair Calibration for Ranking Fairness
Hannah Korevaar, Chris McConnell, Edmund Tong +6
We propose a test of fairness in score-based ranking systems called matched pair calibration. Our approach constructs a set of matched item pairs with minimal confounding differenc…
Cumulative differences between paired samples
Isabel Kloumann, Hannah Korevaar, Chris McConnell +2
The simplest, most common paired samples consist of observations from two populations, with each observed response from one population corresponding to an observed response from th…