SOTAVerified

Zero-shot Generalization

Papers

Showing 151175 of 572 papers

TitleStatusHype
Adapting Segment Anything Model to Multi-modal Salient Object Detection with Semantic Feature Fusion GuidanceCode1
M^3GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and GenerationCode1
MatSAM: Efficient Extraction of Microstructures of Materials via Visual Large ModelCode1
MetaMorph: Learning Universal Controllers with TransformersCode1
Learning the Travelling Salesperson Problem Requires Rethinking GeneralizationCode1
A Multi-Task BERT Model for Schema-Guided Dialogue State TrackingCode1
GOMAA-Geo: GOal Modality Agnostic Active Geo-localizationCode1
FluoroSAM: A Language-aligned Foundation Model for X-ray Image SegmentationCode1
COMPrompter: reconceptualized segment anything model with multiprompt network for camouflaged object detectionCode1
Learning Modular Simulations for Homogeneous SystemsCode1
Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-InCode1
FRESA:Feedforward Reconstruction of Personalized Skinned Avatars from Few ImagesCode1
Equivariant Image ModelingCode1
FRESA: Feedforward Reconstruction of Personalized Skinned Avatars from Few ImagesCode1
Learning Quadrupedal Locomotion over Challenging TerrainCode1
Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text TransformersCode1
From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction TuningCode1
Cross-Lingual Disaster-related Multi-label Tweet Classification with Manifold MixupCode1
LR0.FM: Low-Res Benchmark and Improving Robustness for Zero-Shot Classification in Foundation ModelsCode1
Generalizable Facial Expression RecognitionCode1
Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image SegmentationCode1
Label Agnostic Pre-training for Zero-shot Text ClassificationCode1
Generalization to New Actions in Reinforcement LearningCode1
Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networksCode1
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
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Benchmark Results

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