SOTAVerified

Zero-shot Generalization

Papers

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Showing 501–525 of 572 papers

TitleStatusHype
Improving existing segmentators performance with zero-shot segmentatorsCode0
SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt DenoisingCode0
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction TuningCode0
Data-Free Generalized Zero-Shot LearningCode0
Re-Imagining Multimodal Instruction Tuning: A Representation ViewCode0
Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution ShiftsCode0
Prompt-OT: An Optimal Transport Regularization Paradigm for Knowledge Preservation in Vision-Language Model AdaptationCode0
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive PhysicsCode0
Zero-shot Policy Learning with Spatial Temporal RewardDecomposition on Contingency-aware ObservationCode0
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RLCode0
TRACED: Transition-aware Regret Approximation with Co-learnability for Environment DesignCode0
Prompt Learning for Generalized Vehicle RoutingCode0
Prohibited Items Segmentation via Occlusion-aware Bilayer ModelingCode0
PoseLLM: Enhancing Language-Guided Human Pose Estimation with MLP AlignmentCode0
Image-Caption Encoding for Improving Zero-Shot GeneralizationCode0
Segment anything model for head and neck tumor segmentation with CT, PET and MRI multi-modality imagesCode0
One Shot is Enough for Sequential Infrared Small Target SegmentationCode0
Zero-shot generalization across architectures for visual classificationCode0
OLIVE: Object Level In-Context Visual EmbeddingsCode0
Zero-Shot Generalization during Instruction Tuning: Insights from Similarity and GranularityCode0
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask DependenciesCode0
Octavius: Mitigating Task Interference in MLLMs via LoRA-MoECode0
SemSup: Semantic Supervision for Simple and Scalable Zero-shot GeneralizationCode0
Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuliCode0
Convolutional Conditional Neural ProcessesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GR-MGAvg. sequence length4.04—Unverified
2MoDEAvg. sequence length4.01—Unverified
3RoboUniViewAvg. sequence length3.65—Unverified
43D Diffuser ActorAvg. sequence length3.27—Unverified
5GR-1Avg. sequence length3.06—Unverified