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Training Language Models to Follow Instructions with Human Feedback
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FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
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Competition-Level Code Generation with AlphaCode
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Low-Overhead Fault-Tolerant Quantum Error Correction with the Surface-GKP Code
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Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
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ML-Decoder: Scalable and Versatile Classification Head
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A Mathematical Framework for Transformer Circuits
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Training Verifiers to Solve Math Word Problems
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Improving language models by retrieving from trillions of tokens
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ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
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On-device Panoptic Segmentation for Camera Using Transformers
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Merlion: A Machine Learning Library for Time Series
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Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
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AGENT: A Benchmark for Core Psychological Reasoning
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Highly accurate protein structure predictionwith AlphaFold
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LoRA: Low-Rank Adaptation of Large Language Models
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AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE
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M6: A Chinese Multimodal Pretrainer
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Holographic dynamics simulations with a trapped ion quantum computer
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An autonomous debating system (Project Debater)
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Learning Transferable Visual Models From Natural Language Supervision
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Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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Scalable Differential Privacy with Certified Robustness in Adversarial Learning
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PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest
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Denoising Diffusion Probabilistic Models
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ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
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NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
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Scaling Laws for Neural Language Models
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Dota 2 with Large Scale Deep Reinforcement Learning
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
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Overton: A Data System for Monitoring and Improving Machine-Learned Products
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StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
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RoBERTa: A Robustly Optimized BERT Pretraining Approach
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D2-Net: A Trainable CNN for Joint Description and Detection of Local FeaturesMicrosoft / Chalmers University of Technology, Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University, Département d'Informatique de l'ENS, ETH Zurich, Institute of Science Tokyo, National Institute for Research in Digital Science and Technology
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The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
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DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
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AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
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Improving Language Understanding by Generative Pre-Training (GPT-1)
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Evaluating Discourse Phenomena in Neural Machine Translation
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Deep Sets
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Language Models are Unsupervised Multitask Learners
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Mask R-CNN
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Billion-scale similarity search with GPUs
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High Speed All-optical extended DV-Curve-based DNA sequence alignment utilizing wavelength and polarization modulation
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Learning with Privacy at Scale
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Proximal Policy Optimization Algorithms
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Learning from Simulated and Unsupervised Images through Adversarial Training
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Attention Is All You Need
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
