model size

Prune Wisely, Reconstruct Sharply: Compact 3D Gaussian Splatting via Adaptive Pruning and Difference-of-Gaussian Primitives CVPR 2026 Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough? ICML 2025 Efficient and Separate Authentication Image Steganography Network ICML 2025 Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving ICML 2025 Radio: Rate–Distortion Optimization for Large Language Model Compression ICML 2025 Scaling Laws for Pre-training Agents and World Models ICML 2025 SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators ICLR 2025 Towards Precise Scaling Laws for Video Diffusion Transformers CVPR 2025 A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts ICML 2024 Contemplative Mechanism for Speech Recognition: Speech Encoders can Think Interspeech 2024 Do Efficient Transformers Really Save Computation? ICML 2024 Generalization to New Sequential Decision Making Tasks with In-Context Learning ICML 2024 Resolving Discrepancies in Compute-Optimal Scaling of Language Models NeurIPS 2024 Scaling Laws for Fine-Grained Mixture of Experts ICML 2024 STEER: Assessing the Economic Rationality of Large Language Models ICML 2024 Towards Establishing Guaranteed Error for Learned Database Operations ICLR 2024 Mapping Brains with Language Models: A Survey ACL 2023 Scaling Laws for Multilingual Neural Machine Translation ICML 2023 Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias NAACL 2022 Deep Double Descent: Where Bigger Models and More Data Hurt ICLR 2020 Utility is in the Eye of the User: A Critique of NLP Leaderboards EMNLP 2020 Dual Space Gradient Descent for Online Learning NeurIPS 2016 Fixed Point Quantization of Deep Convolutional Networks ICML 2016