model scaling

AI Model Factory: Scaling AI for Industry 4.0 Applications AAAI 2023 Boosting Single Image Super-Resolution via Partial Channel Shifting ICCV 2023 Causes and Cures for Interference in Multilingual Translation ACL 2023 Exploring the Impact of Model Scaling on Parameter-Efficient Tuning EMNLP 2023 Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages ACL 2023 How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench EMNLP 2023 Mapping Brains with Language Models: A Survey ACL 2023 Model Analysis & Evaluation for Ambiguous Question Answering ACL 2023 MoEC: Mixture of Expert Clusters AAAI 2023 On the Benefits of Learning to Route in Mixture-of-Experts Models EMNLP 2023 Quantifying Memorization Across Neural Language Models ICLR 2023 Reproducible Scaling Laws for Contrastive Language-Image Learning CVPR 2023 Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale ACL 2023 Revisiting Non-Autoregressive Translation at Scale ACL 2023 RT-1: Robotics Transformer for Real-World Control at Scale RSS 2023 Scale Alone Does not Improve Mechanistic Interpretability in Vision Models NeurIPS 2023 Scaling Language-Image Pre-Training via Masking CVPR 2023 Scaling Law for Document Neural Machine Translation EMNLP 2023 Scaling Laws for Multilingual Neural Machine Translation ICML 2023 Scaling Up Models and Data with t5x and seqio JMLR 2023 Scaling Vision-Language Models with Sparse Mixture of Experts EMNLP 2023 Scaling Vision Transformers to 22 Billion Parameters ICML 2023 SLAMB: Accelerated Large Batch Training with Sparse Communication ICML 2023 To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis NeurIPS 2023 Toward Large Kernel Models ICML 2023