mlsanityData to 14 Oct 2026

PLACO: A Multi-Stage Framework for Cost-Effective Performance in Human-AI Teams

arXiv 2605.08388 ↗First posted 8 May 2026cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Human-AI teams play a pivotal role in improving overall system performance when neither the human nor the model can achieve such performance on their own. With the advent of powerful and accessible Generative AI models, several mundane tasks have morphed into Human-AI team tasks. From writing essays to developing advanced algorithms, humans have found that using AI assistance has led to an accelerated work pace like never before. In classification tasks, where the final output is a single hard label, it is crucial to address the combination of human and model output. Prior work elegantly solves this problem using Bayes rule, using the assumption that human and model output are conditionally independent given the ground truth. Specifically, it discusses a combination method to combine a single deterministic labeler (the human) and a probabilistic labeler (the classifier model) using the model's instance-level and the human's class-level calibrated probabilities.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 30 references that are in the map. First posted on arXiv 8 May 2026.

Builds on

15 of 30 references.

References · 15

  1. 2016A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networkscited by 2,385
  2. 2020Consistent Estimators for Learning to Defer to an Expertcited by 271
  3. 2017Predict Responsibly: Improving Fairness and Accuracy by Learning to Defercited by 233
  4. 2021A Survey of Human-in-the-loop for Machine Learningcited by 215
  5. 2021Towards Unbiased and Accurate Deferral to Multiple Expertscited by 72
  6. 2022Calibrated Learning to Defer with One-vs-All Classifierscited by 69
  7. 2021Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibrationcited by 40
  8. 2022Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Expertscited by 40
  9. 2021Human-AI Collaboration with Bandit Feedbackcited by 36
  10. 2021Role of Human-AI Interaction in Selective Predictioncited by 35
  11. 2022On the Utility of Prediction Sets in Human-AI Teamscited by 34
  12. 2023Learning to Defer with Limited Expert Predictionscited by 25
3 more
  1. 2022Human-AI Collaboration in Decision-Making: Beyond Learning to Defercited by 16
  2. 2024A2C: A Modular Multi-stage Collaborative Decision Framework for Human-AI Teamscited by 12
  3. 2024Optimizing Risk-averse Human-AI Hybrid Teamscited by 1

Built on by

Not cited yet.