Co-occurring keywords · papers mentioning both
Papers
FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
NeurIPS 2024
GLID: Pre-training a Generalist Encoder-Decoder Vision Model
CVPR 2024
Language-guided Manipulator Motion Planning with Bounded Task Space
CoRL 2024
Language Model as Visual Explainer
NeurIPS 2024
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
NeurIPS 2024
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
NeurIPS 2024
On the Use of Anchoring for Training Vision Models
NeurIPS 2024
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization
ICML 2024
Position: Do Not Explain Vision Models Without Context
ICML 2024
Pre-training Differentially Private Models with Limited Public Data
NeurIPS 2024
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data
NeurIPS 2024
ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation
CoRL 2024
Scalable Pre-training of Large Autoregressive Image Models
ICML 2024
TrAct: Making First-layer Pre-Activations Trainable
NeurIPS 2024
VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation
CVPR 2024
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
NeurIPS 2024
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
CoRL 2024
When does perceptual alignment benefit vision representations?
NeurIPS 2024
A Whac-a-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others
CVPR 2023
Exploring Geometry of Blind Spots in Vision models
NeurIPS 2023
Improving CLIP Training with Language Rewrites
NeurIPS 2023
Linguistic More: Taking a Further Step toward Efficient and Accurate Scene Text Recognition
IJCAI 2023
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
NeurIPS 2023
On Data Scaling in Masked Image Modeling
CVPR 2023
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models
NeurIPS 2023