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 111–120 of 158 papers

TitleStatusHype
Can Machines Design? An Artificial General Intelligence Approach—0
CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning—0
Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenon—0
Privacy-Enabled Biometric Search—0
Prototype Recalls for Continual Learning—0
25 years of criticality in neuroscience -- established results, open controversies, novel concepts—0
Reaction Network Analysis of Metabolic Insulin Signaling—0
Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence—0
Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems—0
A Robust, Efficient Predictive Safety Filter—0
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