Papers

Filtered to memory architectures · clear filter

Browse by term

continual learning 64reinforcement learning 34large language models 17benchmarking 12vision-language models 10generative models 8language models 8video generation 7multimodal models 6natural language processing 6robotics 6world models 6benchmarks 5diffusion models 5on-policy distillation 5policy optimization 5scalability 5self-distillation 5vision-language-action models 5autoregressive models 4computer vision 4diffusion transformers 4LLMs 4multimodal large language models 4verifiable rewards 4attention mechanisms 3embodied intelligence 3image editing 3long-term memory 3multimodal learning 3

Matching papers

Memory for Large Language Models

8 upvotes · 28 JUL 2026 · Sining Zhoubian, Dan Zhang, Evgeny Kharlamov et al.

This paper creates a systematic framework for understanding memory in large language models, helping researchers design more scalable and adaptive language models. Practitioners might care because it provides a unified perspective on memory mechanisms, making it easier to evaluate and improve language model performance.

large language modelsmemory architecturesnatural language processingmachine learning modelscomputational memory