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

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Showing 51–75 of 158 papers

TitleStatusHype
BOWLL: A Deceptively Simple Open World Lifelong LearnerCode0
Simple and Lightweight Human Pose EstimationCode0
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training DataCode0
Decoupled Novel Object CaptionerCode0
How Should Agents Ask Questions For Situated Learning? An Annotated Dialogue CorpusCode0
A Provable Defense for Deep Residual NetworksCode0
NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional GeneralizationCode0
Neural Concept Formation in Knowledge GraphsCode0
Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of ImagesCode0
Knowledge Graph Transfer Network for Few-Shot RecognitionCode0
A Clustering-based Framework for Classifying Data StreamsCode0
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature SpaceCode0
Multi-level Semantic Feature Augmentation for One-shot LearningCode0
SketchEmbedNet: Learning Novel Concepts by Imitating DrawingsCode0
Continual Zero-Shot Learning through Semantically Guided Generative Random WalksCode0
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations—0
Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—0
Exploring internal representation of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects—0
Explaining deep neural network models for electricity price forecasting with XAI—0
Coherent Temporal Synthesis for Incremental Action Segmentation—0
Experimental Contexts Can Facilitate Robust Semantic Property Inference in Language Models, but Inconsistently—0
Experiencing Urban Air Mobility: How Passengers evaluate a simulated flight with an Air Taxi—0
Error Analysis of Shapley Value-Based Model Explanations: An Informative Perspective—0
Enhancing Balanced Graph Edge Partition with Effective Local Search—0
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