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 1120 of 158 papers

TitleStatusHype
Dynamic Few-Shot Visual Learning without ForgettingCode1
DreamCreature: Crafting Photorealistic Virtual Creatures from ImaginationCode1
A Language Model's Guide Through Latent SpaceCode1
Happy: A Debiased Learning Framework for Continual Generalized Category DiscoveryCode1
EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and IndexingCode1
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and ReasoningCode1
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object InteractionsCode1
Extract Free Dense Labels from CLIPCode1
LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object DetectionCode1
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual LearningCode1
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