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Zero-shot Generalization

Papers

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Showing 376–400 of 572 papers

TitleStatusHype
Enhancing Robustness of Vision-Language Models through Orthogonality Learning and Self-Regularization—0
Real-Time Anomaly Detection and Reactive Planning with Large Language Models—0
Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object SearchCode0
Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieval—0
NeuralSCF: Neural network self-consistent fields for density functional theory—0
Zero-Shot Generalization during Instruction Tuning: Insights from Similarity and GranularityCode0
Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers—0
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction TuningCode0
Prompt-based Visual Alignment for Zero-shot Policy Transfer—0
OLIVE: Object Level In-Context Visual EmbeddingsCode0
Text-only Synthesis for Image Captioning—0
TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability—0
Benchmarking General-Purpose In-Context Learning—0
Amortized Active Causal Induction with Deep Reinforcement Learning—0
Gradient Projection For Continual Parameter-Efficient Tuning—0
Prompt Learning for Generalized Vehicle RoutingCode0
Revisiting the Robust Generalization of Adversarial Prompt Tuning—0
A Minimalist Prompt for Zero-Shot Policy Learning—0
Enhancing Vision-Language Models Generalization via Diversity-Driven Novel Feature Synthesis—0
Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific TasksCode0
The Third Monocular Depth Estimation Challenge—0
Enabling Natural Zero-Shot Prompting on Encoder Models via Statement-Tuning—0
Inferring Behavior-Specific Context Improves Zero-Shot Generalization in Reinforcement LearningCode0
PromptSync: Bridging Domain Gaps in Vision-Language Models through Class-Aware Prototype Alignment and Discrimination—0
DiffCJK: Conditional Diffusion Model for High-Quality and Wide-coverage CJK Character Generation—0
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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