OLAPH: Improving Factuality in Biomedical Long-form Question Answering

[PDF] arxiv.org

Large language model validity via enhanced conformal prediction methods

JJ Cherian, I Gibbs, EJ Candès - arXiv preprint arXiv:2406.09714, 2024 - arxiv.org
We develop new conformal inference methods for obtaining validity guarantees on the
output of large language models (LLMs). Prior work in conformal language modeling …
被引用次数：8 相关文章
[PDF] arxiv.org

LLMs are not Zero-Shot Reasoners for Biomedical Information Extraction

A Nagar, V Schlegel, TT Nguyen, H Li, Y Wu… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) are increasingly adopted for applications in healthcare,
reaching the performance of domain experts on tasks such as question answering and …
相关文章 所有 2 个版本
[PDF] arxiv.org

HALO: Hallucination Analysis and Learning Optimization to Empower LLMs with Retrieval-Augmented Context for Guided Clinical Decision Making

S Anjum, H Zhang, W Zhou, EJ Paek, X Zhao… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) have significantly advanced natural language processing
tasks, yet they are susceptible to generating inaccurate or unreliable responses, a …
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[PDF] arxiv.org

Culinary Class Wars: Evaluating LLMs using ASH in Cuisine Transfer Task

H Lee, M Gim, D Park, D Choi, J Kang - arXiv preprint arXiv:2411.01996, 2024 - arxiv.org
The advent of Large Language Models (LLMs) have shown promise in various creative
domains, including culinary arts. However, many LLMs still struggle to deliver the desired …
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