Stream-CQSA: Exact Out-of-Memory Recovery for Attention
cs.LG, cs.DC
Submitted: 2026-04-22
Updated: 2026-09-01
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Scaling Laws for Neural Language Models
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Qwen3 Technical Report
- FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
- Longformer: The Long-Document Transformer
- LongNet: Scaling Transformers to 1,000,000,000 Tokens
- Linformer: Self-Attention with Linear Complexity
- Reformer: The Efficient Transformer
- Rethinking Attention with Performers
- LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
- Efficient Streaming Language Models with Attention Sinks
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