54 citations · 56 across the 11 of their papers we have counts for
11 papers
Scoring Rules! Statistical and Strategic Alignment for Text Evaluation Metrics
Shengwei Xu, Yuxuan Lu, Yifan Wu +2
Reference-based text evaluation metrics, which are widely used to assess natural language generation systems, score a candidate response by comparing it with a reference response.…
To Reason or Not to: Selective Chain-of-Thought in Medical Question Answering
Zaifu Zhan, Min Zeng, Shuang Zhou +6
Objective: To improve the efficiency of medical question answering (MedQA) with large language models (LLMs) by avoiding unnecessary reasoning while maintaining accuracy. Methods:…
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…
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…
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…
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…
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…
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.…
Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis
Priyanka Nanayakkara, Hyeok Kim, Yifan Wu +4
Differential privacy (DP) has the potential to enable privacy-preserving analysis on sensitive data, but requires analysts to judiciously spend a limited ``privacy loss budget'' $ε…
ElicitationGPT: Text Elicitation Mechanisms via Language Models
Yifan Wu, Jason Hartline
Scoring rules evaluate probabilistic forecasts of an unknown state against the realized state and are a fundamental building block in the incentivized elicitation of information. T…
A Decision Theoretic Framework for Measuring AI Reliance
Ziyang Guo, Yifan Wu, Jason Hartline +1
Humans frequently make decisions with the aid of artificially intelligent (AI) systems. A common pattern is for the AI to recommend an action to the human who retains control over…