9 citations · 10 across the 8 of their papers we have counts for
9 papers
Efficient Evaluation of LLM Performance with Statistical Guarantees
Skyler Wu, Yash Nair, Emmanuel J. Candès
Exhaustively evaluating many large language models (LLMs) on a large suite of benchmarks is expensive. We cast benchmarking as finite-population inference and, under a fixed query…
Intelligently Weighting Multiple Reference Models for Direct Preference Optimization of LLMs
Skyler Wu, Aymen Echarghaoui
Fine-tuning is integral for aligning large language models (LLMs) with human preferences. Multiple-Reference Preference Optimization (MRPO) builds on Direct Preference Optimization…
Missing Data Multiple Imputation for Tabular Q-Learning in Online RL
Kyla Chasalow, Skyler Wu, Susan Murphy
Missing data in online reinforcement learning (RL) poses challenges compared to missing data in standard tabular data or in offline policy learning. The need to impute and act at e…
Parallelizing MCMC Across the Sequence Length
David M. Zoltowski, Skyler Wu, Xavier Gonzalez +2
Markov chain Monte Carlo (MCMC) methods are foundational algorithms for Bayesian inference and probabilistic modeling. However, most MCMC algorithms are inherently sequential and t…
Are Statistical Methods Obsolete in the Era of Deep Learning? A Study of ODE Inverse Problems
Skyler Wu, Shihao Yang, S. C. Kou
In the era of AI, neural networks have become increasingly popular for modeling, inference, and prediction, largely due to their potential for universal approximation. With the pro…
Stabilizing Linear Passive-Aggressive Online Learning with Weighted Reservoir Sampling
Skyler Wu, Fred Lu, Edward Raff +1
Online learning methods, like the seminal Passive-Aggressive (PA) classifier, are still highly effective for high-dimensional streaming data, out-of-core processing, and other thro…
Extracting Signal out of Chaos: Advancements on MAGI for Bayesian Analysis of Dynamical Systems
Skyler Wu
This work builds off the manifold-constrained Gaussian process inference (MAGI) method for Bayesian parameter inference and trajectory reconstruction of ODE-based dynamical systems…
Exploring the Sharpened Cosine Similarity
Skyler Wu, Fred Lu, Edward Raff +1
Convolutional layers have long served as the primary workhorse for image classification. Recently, an alternative to convolution was proposed using the Sharpened Cosine Similarity…
Analyzing Chain-of-Thought Prompting in Large Language Models via Gradient-based Feature Attributions
Skyler Wu, Eric Meng Shen, Charumathi Badrinath +2
Chain-of-thought (CoT) prompting has been shown to empirically improve the accuracy of large language models (LLMs) on various question answering tasks. While understanding why CoT…