#Model Optimization
Latest news articles tagged with "Model Optimization". Follow the timeline of events, related topics, and entities.
Articles (9)
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🇺🇸 Invariant Transformation and Resampling based Epistemic-Uncertainty Reduction
[USA]
arXiv:2602.23315v1 Announce Type: new Abstract: An artificial intelligence (AI) model can be viewed as a function that maps inputs to outputs in high-dimensional spaces. Once designed and well traine...
Related: #Artificial Intelligence, #Uncertainty Reduction -
🇺🇸 Elimination-compensation pruning for fully-connected neural networks
[USA]
arXiv:2602.20467v1 Announce Type: cross Abstract: The unmatched ability of Deep Neural Networks in capturing complex patterns in large and noisy datasets is often associated with their large hypothes...
Related: #Machine Learning, #Neural Networks -
🇺🇸 Understanding vs. Generation: Navigating Optimization Dilemma in Multimodal Models
[USA]
arXiv:2602.15772v1 Announce Type: cross Abstract: Current research in multimodal models faces a key challenge where enhancing generative capabilities often comes at the expense of understanding, and ...
Related: #Multimodal AI, #Generation vs. Understanding, #Reasoning and Reflection, #Trade‑off Analysis -
🇺🇸 Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders
[USA]
arXiv:2507.03262v4 Announce Type: replace-cross Abstract: Recent multimodal large language models (MLLMs) increasingly integrate multiple vision encoders to improve performance on various benchmarks,...
Related: #AI Efficiency, #Multimodal Learning -
🇺🇸 Weak-Driven Learning: How Weak Agents make Strong Agents Stronger
[USA]
arXiv:2602.08222v1 Announce Type: new Abstract: As post-training optimization becomes central to improving large language models, we observe a persistent saturation bottleneck: once models grow highl...
Related: #Artificial Intelligence, #Machine Learning -
🇺🇸 HQP: Sensitivity-Aware Hybrid Quantization and Pruning for Ultra-Low-Latency Edge AI Inference
[USA]
arXiv:2602.06069v1 Announce Type: cross Abstract: The escalating demand for high-fidelity, real-time inference in distributed edge-cloud environments necessitates aggressive model optimization to cou...
Related: #Artificial Intelligence, #Edge Computing -
🇺🇸 POP: Online Structural Pruning Enables Efficient Inference of Large Foundation Models
[USA]
arXiv:2602.06822v1 Announce Type: new Abstract: Large foundation models (LFMs) achieve strong performance through scaling, yet current structural pruning methods derive fixed pruning decisions during...
Related: #Artificial Intelligence, #Computer Science -
🇺🇸 Learning Rate Scaling across LoRA Ranks and Transfer to Full Finetuning
[USA]
arXiv:2602.06204v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a standard tool for parameter-efficient finetuning of large models. While it induces a small memory footprint, its trai...
Related: #Machine Learning, #Artificial Intelligence -
🇺🇸 When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging
[USA]
arXiv:2602.05536v1 Announce Type: cross Abstract: Model merging combines multiple fine-tuned models into a single model by adding their weight updates, providing a lightweight alternative to retraini...
Related: #Artificial Intelligence, #Machine Learning