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 131140 of 158 papers

TitleStatusHype
Meta-Learning by Hallucinating Useful Examples0
Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks0
Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems0
Task-Aware Feature Generation for Zero-Shot Compositional LearningCode0
Variational Prototype Replays for Continual LearningCode0
Task-Driven Modular Networks for Zero-Shot Compositional LearningCode0
A Provable Defense for Deep Residual NetworksCode0
25 years of criticality in neuroscience -- established results, open controversies, novel concepts0
Situational Grounding within Multimodal Simulations0
Understanding MCMC Dynamics as Flows on the Wasserstein SpaceCode0
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