Co-occurring keywords · papers mentioning both
Papers
Multi-Head Mixture-of-Experts
NeurIPS 2024
On Feature Learning in Structured State Space Models
NeurIPS 2024
On Scaling Up a Multilingual Vision and Language Model
CVPR 2024
On the Scalability of Diffusion-based Text-to-Image Generation
CVPR 2024
On the Scaling Laws of Geographical Representation in Language Models
COLING 2024
Quantifying Association Capabilities of Large Language Models and Its Implications on Privacy Leakage
EACL 2024
Revisiting Adversarial Training at Scale
CVPR 2024
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
NeurIPS 2024
ScaleKD: Strong Vision Transformers Could Be Excellent Teachers
NeurIPS 2024
Scaling Instruction-Finetuned Language Models
JMLR 2024
Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations
NeurIPS 2024
Scaling Laws for Sparsely-Connected Foundation Models
ICLR 2024
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
NeurIPS 2024
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
CVPR 2024
Scaling White-Box Transformers for Vision
NeurIPS 2024
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
NAACL 2024
Sparse maximal update parameterization: A holistic approach to sparse training dynamics
NeurIPS 2024
Tending Towards Stability: Convergence Challenges in Small Language Models
EMNLP 2024
The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning
ICLR 2024
Tokenization Falling Short: On Subword Robustness in Large Language Models
EMNLP 2024
Transformer verbatim in-context retrieval across time and scale
CoNLL 2024
Understanding Emergent Abilities of Language Models from the Loss Perspective
NeurIPS 2024
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling
NeurIPS 2024
When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale
NAACL 2024
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
ICLR 2024