transformer

One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning ICML 2024 On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions ICML 2024 PIDformer: Transformer Meets Control Theory ICML 2024 PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds CoRL 2024 PoliFormer: Scaling On-Policy RL with Transformers Results in Masterful Navigators CoRL 2024 Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning ICML 2024 Privacy Backdoors: Stealing Data with Corrupted Pretrained Models ICML 2024 Prompting a Pretrained Transformer Can Be a Universal Approximator ICML 2024 Q-SLAM: Quadric Representations for Monocular SLAM CoRL 2024 Q-value Regularized Transformer for Offline Reinforcement Learning ICML 2024 Repeat After Me: Transformers are Better than State Space Models at Copying ICML 2024 Rethinking Transformers in Solving POMDPs ICML 2024 Retrieval Robust to Object Motion Blur ECCV 2024 SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention ICML 2024 Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers ICML 2024 Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation CoRL 2024 Scaling Rectified Flow Transformers for High-Resolution Image Synthesis ICML 2024 Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection ECCV 2024 Simulation of Graph Algorithms with Looped Transformers ICML 2024 Spline-based Transformers ECCV 2024 Tandem Transformers for Inference Efficient LLMs ICML 2024 The Illusion of State in State-Space Models ICML 2024 The Pitfalls of Next-Token Prediction ICML 2024 Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model ICML 2024 Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention ICML 2024