Search Results for author:
Found 2 papers, 2 papers with code
Uncertainty Awareness of Large Language Models Under Code Distribution Shifts: A Benchmark Study
We observe that these methods generally improve the uncertainty awareness of CodeLlama, with increased calibration quality and higher uncertainty estimation~(UE) precision.
Distantly-Supervised Joint Extraction with Noise-Robust Learning
Joint entity and relation extraction is a process that identifies entity pairs and their relations using a single model.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
