Carlos Guestrin

Learning to Discover at Test Time

arXiv 2026

Reinforcement Learning via Self-Distillation

arXiv 2026

PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models

arXiv 2026

DeepScholar-Bench: A Live Benchmark and Automated Evaluation for Generative Research Synthesis

arXiv 2025

One-Minute Video Generation with Test-Time Training

CVPR 2025 1

End-to-End Test-Time Training for Long Context

arXiv 2025

Obfuscated Activations Bypass LLM Latent-Space Defenses

arXiv 2024

Benchmarking Distributional Alignment of Large Language Models

arXiv 2024

TextGrad: Automatic "Differentiation" via Text

arXiv 2024

Semantic Operators: A Declarative Model for Rich, AI-based Data Processing

arXiv 2024

Learning to (Learn at Test Time): RNNs with Expressive Hidden States

arXiv 2024

Text2SQL is Not Enough: Unifying AI and Databases with TAG

arXiv 2024

Learning to (Learn at Test Time)

arXiv 2023

XGBoost: A Scalable Tree Boosting System

arXiv 2016

"Why Should I Trust You?": Explaining the Predictions of Any Classifier

arXiv 2016

Tatsunori Hashimoto

professor

Xiaolong Wang

Yu Sun

Karan Dalal

Sanmi Koyejo

professor

Xinhao Li

Daniel Koceja

Liana Patel

Matei Zaharia

founder

Yejin Choi

professor