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Toward Understanding the Influence of Individual Clients in Federated Learning., , , , , , and . CoRR, (2020)FactCHD: Benchmarking Fact-Conflicting Hallucination Detection., , , , , , , , , and . CoRR, (2023)INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile Devices., , , , , , , , , and 1 other author(s). CoRR, (2020)AUTOACT: Automatic Agent Learning from Scratch via Self-Planning., , , , , , , and . CoRR, (2024)Secure Federated Submodel Learning., , , , , , , and . CoRR, (2019)Federated Submodel Averaging., , , , , , and . CoRR, (2021)Billion-scale federated learning on mobile clients: a submodel design with tunable privacy., , , , , , , and . MobiCom, page 31:1-31:14. ACM, (2020)IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination., , , , , , and . CoRR, (2024)GaussianTalker: Speaker-specific Talking Head Synthesis via 3D Gaussian Splatting., , , , , , , , , and 1 other author(s). CoRR, (2024)MNN: A Universal and Efficient Inference Engine., , , , , , , , , and 2 other author(s). CoRR, (2020)