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Found 5 papers, 0 papers with code
Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation
We hypothesize that the underlying phenomenological coverage has not been proportionally scaled up, leading to a skew of the presented phenomenon which harms generalization.
Aligner: One Global Token is Worth Millions of Parameters When Aligning Large Language Models
We introduce Aligner, a novel Parameter-Efficient Fine-Tuning (PEFT) method for aligning multi-billion-parameter-sized Large Language Models (LLMs).
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
Training energy-based models (EBMs) on high-dimensional data can be both challenging and time-consuming, and there exists a noticeable gap in sample quality between EBMs and other generative frameworks like GANs and diffusion models.
Progressive Energy-Based Cooperative Learning for Multi-Domain Image-to-Image Translation
The components of translator, style encoder, and style generator constitute a diversified image generator.
Robust Transfer Learning with Pretrained Language Models through Adapters
Transfer learning with large pretrained transformer-based language models like BERT has become a dominating approach for most NLP tasks.
