activity
20242026
most citedVMC: A Grammar for Visualizing Statistical Model Checks

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 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.AI2025

Explanations are a Means to an End: Decision Theoretic Explanation Evaluation

Ziyang Guo, Berk Ustun, Jessica Hullman

Explanations of model behavior are commonly evaluated via proxy properties weakly tied to the purposes explanations serve in practice. We contribute a decision theoretic framework…

cs.LG2025

Conformal Prediction and Human Decision Making

Jessica Hullman, Yifan Wu, Dawei Xie +2

Methods to quantify uncertainty in predictions from arbitrary models are in demand in high-stakes domains like medicine and finance. Conformal prediction has emerged as a popular m…

cs.AI2025

Explaining and Improving Information Complementarities in Multi-Agent Decision-making

Ziyang Guo, Yifan Wu, Jason Hartline +1

Multiple agents are increasingly combined to make decisions with the expectation of achieving complementary performance, where the decisions they make together outperform those mad…

cs.HC2024

Unexploited Information Value in Human-AI Collaboration

Ziyang Guo, Yifan Wu, Jason Hartline +1

Humans and AIs are often paired on decision tasks with the expectation of achieving complementary performance -- where the combination of human and AI outperforms either one alone.…

cs.HC20241 cited

VMC: A Grammar for Visualizing Statistical Model Checks

Ziyang Guo, Alex Kale, Matthew Kay +1

Visualizations play a critical role in validating and improving statistical models. However, the design space of model check visualizations is not well understood, making it diffic…