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FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting is the primary contribution described in this paper.

We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.

We present Unified Latents (UL), a framework for learning latent representations that are jointly regularized by a diffusion prior and decoded by a diffusion model.

Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials.

Attention-based Extraction of Structured Information from Street View Imagery presents a transformer method.

Recent work on adversarial attack has shown that Projected Gradient Descent (PGD) Adversary is a universal first-order adversary, and the classifier adversarially trained by PGD i…

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators is the primary contribution described in this paper.

UL2: Unifying Language Learning Paradigms is the primary contribution described in this paper.

Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones is the primary contribution described in this paper.

Masked Diffusion Models (MDMs) offer greater flexibility in decoding order than autoregressive models but require careful planning to achieve high-quality generation.

Continual Learning (CL) with large-scale pre-trained models (PTMs) has recently gained wide attention, shifting the focus from training from scratch to continually adapting PTMs.

Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression is the primary contribution described in this paper.