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 31–40 of 158 papers

TitleStatusHype
Error Analysis of Shapley Value-Based Model Explanations: An Informative Perspective—0
Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenon—0
Sketch-Plan-Generalize: Learning and Planning with Neuro-Symbolic Programmatic Representations for Inductive Spatial Concepts—0
Hyperbolic Learning with Synthetic Captions for Open-World Detection—0
Is CLIP the main roadblock for fine-grained open-world perception?Code2
Attention Calibration for Disentangled Text-to-Image PersonalizationCode2
Coherent Temporal Synthesis for Incremental Action Segmentation—0
A Language Model's Guide Through Latent SpaceCode1
Theoretical and Empirical Analysis of Adaptive Entry Point Selection for Graph-based Approximate Nearest Neighbor Search—0
BOWLL: A Deceptively Simple Open World Lifelong LearnerCode0
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