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 7180 of 158 papers

TitleStatusHype
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models0
Statistical QoS Provisioning Analysis and Performance Optimization in xURLLC-enabled Massive MU-MIMO Networks: A Stochastic Network Calculus Perspective0
Integrated Planning of Multi-energy Grids: Concepts and Challenges0
Few-Shot Class-Incremental Learning via Class-Aware Bilateral DistillationCode1
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks0
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual LearningCode1
DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter0
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot LearningCode1
Analogical Concept Memory for Architectures Implementing the Common Model of Cognition0
Memorizing Complementation Network for Few-Shot Class-Incremental Learning0
Show:102550
← PrevPage 8 of 16Next →

No leaderboard results yet.