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Achieving 3.8x higher recall with a co-designed framework that integrates graph construction, representation learning, and real-time serving could redefine large-scale recommendation systems.
KVEraser achieves a 3-4x speedup over full recomputation while maintaining high performance in long-context tasks, revolutionizing how we handle context updates in LLMs.
