DualKV is a new FlashAttention variant that shares prompt KV across multiple rollouts in RL training, delivering 1.63-3.82x speedups on 8B-30B models while remaining mathematically identical to standard attention.
Fu, Stefano Ermon, Atri Rudra, and Christopher R \'e
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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RetrievalAttention approximates full attention in long-context LLMs by retrieving relevant KV vectors from CPU-based ANNS indexes with an attention-aware algorithm, achieving near-full accuracy while accessing only 1-3% of the data.
StarCoderBase matches or beats OpenAI's code-cushman-001 on multi-language code benchmarks; the Python-fine-tuned StarCoder reaches 40% pass@1 on HumanEval while retaining other-language performance.
citing papers explorer
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DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts
DualKV is a new FlashAttention variant that shares prompt KV across multiple rollouts in RL training, delivering 1.63-3.82x speedups on 8B-30B models while remaining mathematically identical to standard attention.
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RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval
RetrievalAttention approximates full attention in long-context LLMs by retrieving relevant KV vectors from CPU-based ANNS indexes with an attention-aware algorithm, achieving near-full accuracy while accessing only 1-3% of the data.
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StarCoder: may the source be with you!
StarCoderBase matches or beats OpenAI's code-cushman-001 on multi-language code benchmarks; the Python-fine-tuned StarCoder reaches 40% pass@1 on HumanEval while retaining other-language performance.