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Jilin University, Shanghai Jiao Tong University, University of California at Merced
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Current LLMs struggle to effectively manage memory in multimodal, multi-participant settings, revealing critical gaps in their design.
Forget SVD: CARE aligns low-rank attention approximations with input activations, boosting accuracy up to 1.7x and slashing perplexity by 215x when converting models to multi-head latent attention.
