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 26–50 of 158 papers

TitleStatusHype
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot LearningCode1
XCon: Learning with Experts for Fine-grained Category DiscoveryCode1
ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference TimeCode1
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object InteractionsCode1
EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and IndexingCode1
Learning Instance and Task-Aware Dynamic Kernels for Few Shot LearningCode1
Extract Free Dense Labels from CLIPCode1
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query ShiftCode1
DER: Dynamically Expandable Representation for Class Incremental LearningCode1
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and ReasoningCode1
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot LearningCode1
Dynamic Few-Shot Visual Learning without ForgettingCode1
Explaining deep neural network models for electricity price forecasting with XAI—0
What happens when generative AI models train recursively on each others' generated outputs?—0
From Data to Modeling: Fully Open-vocabulary Scene Graph Generation—0
Neuro-Symbolic Concepts—0
Exploring internal representation of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects—0
Contrastive Visual Data Augmentation—0
Efficient Transmission of Radiomaps via Physics-Enhanced Semantic Communications—0
Towards A Litmus Test for Common Sense—0
Open Ad-hoc Categorization with Contextualized Feature Learning—0
NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional GeneralizationCode0
Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence—0
CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning—0
Knowledge Transfer Across Modalities with Natural Language Supervision—0
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