Evolution and The Knightian Blindspot of Machine Learning
Paper
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2501.13075
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Published
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6
Uncertainty Quantification
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From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
Paper • 2501.03282 • Published -
Efficient Test-Time Scaling via Self-Calibration
Paper • 2503.00031 • Published • 15 -
Investigating Human-Aligned Large Language Model Uncertainty
Paper • 2503.12528 • Published • 4 -
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Paper • 2502.10709 • Published -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Ensemble based approach to quantifying uncertainty of LLM based classifications
Paper • 2502.08631 • Published -
CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought
Paper • 2502.17214 • Published • 1 -
MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs
Paper • 2505.24858 • Published • 17 -
Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits
Paper • 2512.20578 • Published • 83 -
Confidence Estimation for LLMs in Multi-turn Interactions
Paper • 2601.02179 • Published • 16