activity
20232026
most citedExtension of Minimax for Algorithmic Lower Bounds

1 citations · 1 across the 3 of their papers we have counts for

collaborators

9 papers

cs.AI2026

ComplLLM: Fine-tuning LLMs to Discover Complementary Signals for Decision-making

Ziyang Guo, Yifan Wu, Jason Hartline +2

Multi-agent decision pipelines can outperform single agent workflows when complementarity holds, i.e., different agents bring unique information to the table to inform a final deci…

cs.GT2026

Clarification of `Algorithmic Collusion without Threats'

Jason Hartline

This brief note clarifies that the scenario described in Arunachaleswaran et al. (2025) -- titled `Algorithmic Collusion without Threats' -- is not one of collusion, but one where…

cs.LG2025

A Perfectly Truthful Calibration Measure

Jason Hartline, Lunjia Hu, Yifan Wu

Calibration requires that predictions are conditionally unbiased and, therefore, reliably interpretable as probabilities. A calibration measure quantifies how far a predictor is fr…

cs.GT2025

Behavioral Study of Dashboard Mechanisms

Paula Kayongo, Jessica Hullman, Jason Hartline

Visualization dashboards are increasingly used in strategic settings like auctions to enhance decision-making and reduce strategic confusion. This paper presents behavioral experim…

cs.AI2025

Aligned Textual Scoring Rules

Yuxuan Lu, Yifan Wu, Jason Hartline +1

Scoring rules elicit probabilistic predictions from a strategic agent by scoring the prediction against a ground truth state. A scoring rule is proper if, from the agent's perspect…

cs.LG2025

Smooth Calibration and Decision Making

Jason Hartline, Yifan Wu, Yunran Yang

Calibration requires predictor outputs to be consistent with their Bayesian posteriors. For machine learning predictors that do not distinguish between small perturbations, calibra…