3 citations · 9 across the 20 of their papers we have counts for
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From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teaming
Anusha Sinha, Keltin Grimes, James Lucassen +4
A red team simulates adversary attacks to help defenders find effective strategies to defend their systems in a real-world operational setting. As more enterprise systems adopt AI,…
Persona-Augmented Benchmarking: Evaluating LLMs Across Diverse Writing Styles
Kimberly Le Truong, Riccardo Fogliato, Hoda Heidari +1
Current benchmarks for evaluating Large Language Models (LLMs) often do not exhibit enough writing style diversity, with many adhering primarily to standardized conventions. Such b…
Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
Hongyi Henry Jin, Zijun Ding, Dung Daniel Ngo +1
In recent years, multicalibration has emerged as a desirable learning objective for ensuring that a predictor is calibrated across a rich collection of overlapping subpopulations.…
Persuasive Prediction via Decision Calibration
Jingwu Tang, Jiahao Zhang, Fei Fang +1
Bayesian persuasion, a central model in information design, studies how a sender, who privately observes a state drawn from a prior distribution, strategically sends a signal to in…
Dimension-Free Decision Calibration for Nonlinear Loss Functions
Jingwu Tang, Jiayun Wu, Zhiwei Steven Wu +1
When model predictions inform downstream decision making, a natural question is under what conditions can the decision-makers simply respond to the predictions as if they were the…
All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning
Gokul Swamy, Sanjiban Choudhury, Wen Sun +2
From a first-principles perspective, it may seem odd that the strongest results in foundation model fine-tuning (FT) are achieved via a relatively complex, two-stage training proce…
Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage
Konstantina Bairaktari, Jiayun Wu, Zhiwei Steven Wu
Conformal prediction is a powerful distribution-free framework for constructing prediction sets with coverage guarantees. Classical methods, such as split conformal prediction, pro…