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
Grounding Descriptions in Images informs Zero-Shot Visual RecognitionCode1
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object InteractionsCode1
Language-Informed Visual Concept LearningCode1
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic SegmentationCode1
CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent MaskingCode1
DreamCreature: Crafting Photorealistic Virtual Creatures from ImaginationCode1
Extract Free Dense Labels from CLIPCode1
Online Task-Free Continual Generative and Discriminative Learning via Dynamic Cluster MemoryCode1
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot LearningCode1
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