Papers with Bayesian decision theory

2 papers
The neural dynamics of word recognition and integration (2023.emnlp-main)

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Challenge: Using a computational model of word recognition, listeners combine expectations about upcoming content with incremental sensory evidence.
Approach: They fit this model to scalp EEG signals recorded as subjects passively listened to a fictional story and found that words require more than 150 ms of input to be recognized.
Outcome: The proposed model formalizes this perceptual process in Bayesian decision theory and reveals distinct neural processing of words depending on whether or not they can be quickly recognized.
Improving Zero-shot LLM Re-Ranker with Risk Minimization (2024.emnlp-main)

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Challenge: Large Language Models (LLMs) are effective Query Likelihood Models, but their estimation is biased and the model's accuracy is poor.
Approach: They propose a framework which leverages Bayesian decision theory to quantify and mitigate this bias.
Outcome: The proposed framework improves re-ranking, especially in improving the Top-1 accuracy.

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