3 accepted papers
Large Language Models (LLMs) have shown impressive moral reasoning abilities. Yet they often diverge when confronted with complex, multi-factor moral dilemmas. To address these discrepancies, we propose a framework that synthesizes multiple LLMs’ moral judgments into a collectively formulated moral…
A multitude of industries depend on accurate and reasonable tabular data augmentation for their business processes. Contemporary methodologies in generating tabular data revolve around utilizing Generative Adversarial Networks (GAN) or fine-tuning Large Language Models (LLM). However, GAN-based appr…
Recent works on long music audio inpainting have focused on unconditionally generating new segments to inpaint corrupted audio segments. However, the information about these segments may differ significantly from the original. To solve this problem, we propose MAID (Music Audio Inpainting DDPM), a m…