Hardware Race for Scalable Real-Time 3D Neural Reconstruction and Rendering

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Omni-Recon: Harnessing Image-Based Rendering for General-Purpose Neural Radiance Fields

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ORCHES: Orchestrated Test-Time-Compute-based LLM Reasoning on Collaborative GPU-PIM HEterogeneous System

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Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling

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Uni-Render: A Unified Accelerator for Real-Time Rendering Across Diverse Neural Renderers

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Fusion-3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering

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MixRT: Mixed Neural Representations for Real-Time NeRF Rendering

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EyeCoD: Eye Tracking System Acceleration via FlatCam-Based Algorithm and Hardware Co-Design

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GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models

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INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors

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Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction

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ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention

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ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design

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DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference

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EyeCoD: Eye Tracking System Acceleration via FlatCam-based Algorithm and Accelerator Co-Design

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i-FlatCam: A 253 FPS, 91.49 µJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR

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MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input Adaptation

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RT-NeRF: Real-time on-device neural radiance fields towards immersive AR/VR rendering

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2-in-1 accelerator: Enabling random precision switch for winning both adversarial robustness and efficiency

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A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning

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DIAN: Differentiable Accelerator-Network Co-Search towards Maximal DNN Efficiency

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HW-NAS-BENCH: HARDWARE-AWARE NEURAL ARCHITECTURE SEARCH BENCHMARK

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InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks

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Locality Sensitive Teaching

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A new MRAM-based process in-memory accelerator for efficient neural network training with floating point precision

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AutoDNNchip: An automated DNN chip predictor and builder for both FPGAs and ASICs

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DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures

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HALO: Hardware-Aware Learning to Optimize

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SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

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