transformer

Chain-of-Thought Predictive Control ICML 2024 Common Sense Reasoning for Deep Fake Detection ECCV 2024 Controllable Prompt Tuning For Balancing Group Distributional Robustness ICML 2024 Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption ICML 2024 ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy ICML 2024 Delving into Differentially Private Transformer ICML 2024 Denoising Autoregressive Representation Learning ICML 2024 DiffSurf: A Transformer-based Diffusion Model for Generating and Reconstructing 3D Surfaces in Pose ECCV 2024 DiJiang: Efficient Large Language Models through Compact Kernelization ICML 2024 Ditto: Quantization-aware Secure Inference of Transformers upon MPC ICML 2024 Do Transformer World Models Give Better Policy Gradients? ICML 2024 Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series Forecasting MLHC 2024 Emergence of In-Context Reinforcement Learning from Noise Distillation ICML 2024 Emergent Representations of Program Semantics in Language Models Trained on Programs ICML 2024 Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems ICML 2024 Extreme Compression of Large Language Models via Additive Quantization ICML 2024 Few-shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt ECCV 2024 Flexible Residual Binarization for Image Super-Resolution ICML 2024 FrameQuant: Flexible Low-Bit Quantization for Transformers ICML 2024 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning ICML 2024 Graph As Point Set ICML 2024 Graph External Attention Enhanced Transformer ICML 2024 GRiT: A Generative Region-to-text Transformer for Object Understanding ECCV 2024 G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes MLHC 2024 Hierarchical Separable Video Transformer for Snapshot Compressive Imaging ECCV 2024