SOTAVerified

Novel Concepts

Measures the ability of models to uncover an underlying concept that unites several ostensibly disparate entities, which hopefully would not co-occur frequently. This provides a limited test of a model's ability to creatively construct the necessary abstraction to make sense of a situation that it cannot have memorized in training.

Source: BIG-bench

Papers

Showing 2130 of 158 papers

TitleStatusHype
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query ShiftCode1
Extract Free Dense Labels from CLIPCode1
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object InteractionsCode1
Dynamic Few-Shot Visual Learning without ForgettingCode1
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic SegmentationCode1
EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and IndexingCode1
Language-Informed Visual Concept LearningCode1
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual LearningCode1
Happy: A Debiased Learning Framework for Continual Generalized Category DiscoveryCode1
DreamCreature: Crafting Photorealistic Virtual Creatures from ImaginationCode1
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