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Zero-shot Generalization

Papers

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Showing 51–100 of 572 papers

TitleStatusHype
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation CapabilitiesCode2
HybridDepth: Robust Metric Depth Fusion by Leveraging Depth from Focus and Single-Image PriorsCode2
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language ModelsCode2
Unleashing Large-Scale Video Generative Pre-training for Visual Robot ManipulationCode2
GeoBench: Benchmarking and Analyzing Monocular Geometry Estimation ModelsCode2
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal AlignmentCode2
Learning to Route Among Specialized Experts for Zero-Shot GeneralizationCode2
BigBIO: A Framework for Data-Centric Biomedical Natural Language ProcessingCode2
vesselFM: A Foundation Model for Universal 3D Blood Vessel SegmentationCode2
Segment Any Anomaly without Training via Hybrid Prompt RegularizationCode2
SAM2MOT: A Novel Paradigm of Multi-Object Tracking by SegmentationCode2
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion ModelCode2
Autoregressive Image Generation with Randomized Parallel DecodingCode2
RoboUniView: Visual-Language Model with Unified View Representation for Robotic ManipulationCode2
Semantic Guidance Tuning for Text-To-Image Diffusion ModelsCode2
VIMA: General Robot Manipulation with Multimodal PromptsCode2
PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion PreimageCode2
OpenCity: Open Spatio-Temporal Foundation Models for Traffic PredictionCode2
Q-Insight: Understanding Image Quality via Visual Reinforcement LearningCode2
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model PerformanceCode2
Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language ModelCode2
NeRF-Supervised Deep StereoCode2
On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?Code2
EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerceCode2
Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in ClutterCode2
Exploring the Limits of Vision-Language-Action Manipulations in Cross-task GeneralizationCode2
Multitask Prompted Training Enables Zero-Shot Task GeneralizationCode2
Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot LearningCode2
Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite ImageryCode2
Collaborative Decoding Makes Visual Auto-Regressive Modeling EfficientCode2
Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache CompressionCode2
Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask LearningCode2
RSBuilding: Towards General Remote Sensing Image Building Extraction and Change Detection with Foundation ModelCode2
Crosslingual Generalization through Multitask FinetuningCode2
Detecting Everything in the Open World: Towards Universal Object DetectionCode2
Matryoshka Diffusion ModelsCode2
Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model DisentanglementCode2
RecGPT: A Foundation Model for Sequential RecommendationCode2
CLIP-Forge: Towards Zero-Shot Text-to-Shape GenerationCode1
LR0.FM: Low-Res Benchmark and Improving Robustness for Zero-Shot Classification in Foundation ModelsCode1
CLIP-Embed-KD: Computationally Efficient Knowledge Distillation Using Embeddings as TeachersCode1
M^3GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and GenerationCode1
Learning Quadrupedal Locomotion over Challenging TerrainCode1
Learning Modular Simulations for Homogeneous SystemsCode1
Large Language Models are Good Prompt Learners for Low-Shot Image ClassificationCode1
Learning the Travelling Salesperson Problem Requires Rethinking GeneralizationCode1
MAgNet: Mesh Agnostic Neural PDE SolverCode1
Kick Back & Relax: Learning to Reconstruct the World by Watching SlowTVCode1
Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image SegmentationCode1
Boosting Segment Anything Model Towards Open-Vocabulary LearningCode1
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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