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1. Identifying the topological order of quantized half-filled Landau levels through their daughter states

2. StarCoder 2 and The Stack v2: The Next Generation

3. Semi-Supervised Semantic Segmentation via Marginal Contextual Information

4. StarCoder: may the source be with you!

5. GoToNet: Fast Monocular Scene Exposure and Exploration

6. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

7. Graph Representation Learning via Aggregation Enhancement

8. End-to-End Referring Video Object Segmentation with Multimodal Transformers

9. Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels

11. Single-Node Attacks for Fooling Graph Neural Networks

12. Self-Supervised Learning for Large-Scale Unsupervised Image Clustering

13. HCM: Hardware-Aware Complexity Metric for Neural Network Architectures

14. Colored Noise Injection for Training Adversarially Robust Neural Networks

15. Loss Aware Post-training Quantization

16. Smoothed Inference for Adversarially-Trained Models

17. CAT: Compression-Aware Training for bandwidth reduction

18. Feature Map Transform Coding for Energy-Efficient CNN Inference

19. Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks

20. NICE: Noise Injection and Clamping Estimation for Neural Network Quantization

21. UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks

22. Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform

23. Single-node attacks for fooling graph neural networks

27. CAT: Compression-Aware Training for Bandwidth Reduction.

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