3 accepted papers
This work studies how latent space structure impacts the performance of Latent Diffusion Models (LDMs). We show that effective generation requires a latent space that is simultaneously locally smooth, enabling stable and reliable reconstruction, and globally dispersive, allowing the model to draw di
Recent advancements in large language models have revolutionized text generation with their remarkable capabilities. These models can produce controlled texts that closely adhere to specific requirements when prompted appropriately. However, designing an optimal prompt to control multiple attributes…
In extremely low resource relation identification scenario, small language models (SLMs) incline to overfit, which significantly diminishes their accuracy. Recently, large language models (LLMs) are gradually applied to classification tasks with converting original objective into the generation task…