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 91–100 of 158 papers

TitleStatusHype
Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks—0
Coherent Temporal Synthesis for Incremental Action Segmentation—0
Toward enriched Cognitive Learning with XAI—0
Learning to Learn with Compound HD Models—0
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks—0
Linguistically Routing Capsule Network for Out-of-Distribution Visual Question Answering—0
ChatAnything: Facetime Chat with LLM-Enhanced Personas—0
Characterizing the Influence of Features on Reading Difficulty Estimation for Non-native Readers—0
Malware Detection and Prevention using Artificial Intelligence Techniques—0
Memorizing Complementation Network for Few-Shot Class-Incremental Learning—0
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