04 - Loss of Plasticity in Deep Continual Learning
06 - In Search of Lost Domain Generalization
07 - The Augmented Image Prior
11 - 3D Gaussian Splatting for Real-Time Radiance Field Rendering
14 - When and why VLMs behave like BoWs
15 - What Neural Networks Memorize and Why
19 - Hyperbolic Image-Text Representations
21 - How to Scale Your EMA
22 - Do Transformers Really Perform Bad for Graph Representation?
24 - Vision Transformers Need Registers
27 - Learning to Model the World with Language
29 - Fast Inference from Transformers via Speculative Decoding
31 - Simple and Controllable Music Generation
35 - Are Transformers Effective for Time Series Forecasting?
36 - Emergent Abilities of Large Language Models
37 - Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
38 - Can Neural Network Memorization Be Localized?
39 - Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
40 - Adversarial Examples Are Not Bugs, They Are Features
41 - Direct Preference Optimization
43 - Weak-to-Strong Generalization
44 - A Watermark for Large Language Models
45 - Hallucination Detection
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