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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 158 papers

TitleStatusHype
ChatAnything: Facetime Chat with LLM-Enhanced Personas—0
A Closer Look at Rehearsal-Free Continual Learning—0
Characterizing the Influence of Features on Reading Difficulty Estimation for Non-native Readers—0
Characterizing an Analogical Concept Memory for Architectures Implementing the Common Model of Cognition—0
Can Machines Design? An Artificial General Intelligence Approach—0
DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter—0
Automating string processing in spreadsheets using input-output examples—0
Experiencing Urban Air Mobility: How Passengers evaluate a simulated flight with an Air Taxi—0
DRPT: Disentangled and Recurrent Prompt Tuning for Compositional Zero-Shot Learning—0
Experimental Contexts Can Facilitate Robust Semantic Property Inference in Language Models, but Inconsistently—0
Show:102550
← PrevPage 5 of 16Next →

No leaderboard results yet.