Platt scaling
PulseAugur coverage of Platt scaling — every cluster mentioning Platt scaling across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New research advances probability calibration in machine learning
Two new research papers on arXiv explore advancements in the calibration of probability forecasts for machine learning models. The first paper by Nicolò Felicioni introduces a method to estimate second-order calibration…
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Medical VQA models show overconfidence; new calibration method proposed
A new research paper explores the overconfidence and calibration of vision-language models (VLMs) in medical visual question answering (VQA). The study found that overconfidence persists across different model families,…
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LLM uncertainty quantification research explores calibration for reliable answers
Two research papers explore methods for improving the reliability of answers generated by large language models (LLMs), particularly in question-answering tasks. The first paper introduces A-CRC-QA, a post-hoc calibrati…
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IDRAAK framework uses few-shot prompting for semantic drift detection
A new framework called IDRAAK has been developed to detect semantic drift in technical requirements, which can occur during translation and alter critical numerical or modal information. The framework utilizes a languag…
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New KAISEN pipeline enhances fairness auditing for clinical AI models
Researchers have developed KAISEN, a novel five-phase audit pipeline designed to improve the reproducibility and reliability of fairness assessments in clinical risk models. The pipeline addresses subgroup stratificatio…
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New SLC Method Corrects Per-Item Bias in Knowledge Tracing Models
Researchers have developed a new method called State-space Logit Correction (SLC) to address per-item bias in deployed knowledge-tracing models. This bias, arising from architectural limitations and shifts in item prope…