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 51–100 of 158 papers

TitleStatusHype
Surprisal Driven k-NN for Robust and Interpretable Nonparametric Learning—0
A Robust, Efficient Predictive Safety FilterCode0
Towards Open-Ended Visual Recognition with Large Language ModelCode1
ChatAnything: Facetime Chat with LLM-Enhanced Personas—0
Experiencing Urban Air Mobility: How Passengers evaluate a simulated flight with an Air Taxi—0
OV-VG: A Benchmark for Open-Vocabulary Visual GroundingCode1
Continual Zero-Shot Learning through Semantically Guided Generative Random WalksCode0
Link-Context Learning for Multimodal LLMsCode1
CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent MaskingCode1
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature SpaceCode0
Subspace Distillation for Continual LearningCode0
Beneath Surface Similarity: Large Language Models Make Reasonable Scientific Analogies after Structure AbductionCode0
Benchmarking the human brain against computational architectures—0
DRPT: Disentangled and Recurrent Prompt Tuning for Compositional Zero-Shot Learning—0
Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class DiscoveryCode1
IFSeg: Image-free Semantic Segmentation via Vision-Language ModelCode1
Strategy Synthesis in Markov Decision Processes Under Limited Sampling Access—0
WDiscOOD: Out-of-Distribution Detection via Whitened Linear Discriminant AnalysisCode0
LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object DetectionCode1
Influence zones for continuous beam systems—0
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models—0
Statistical QoS Provisioning Analysis and Performance Optimization in xURLLC-enabled Massive MU-MIMO Networks: A Stochastic Network Calculus Perspective—0
Integrated Planning of Multi-energy Grids: Concepts and Challenges—0
Few-Shot Class-Incremental Learning via Class-Aware Bilateral DistillationCode1
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks—0
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual LearningCode1
DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter—0
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot LearningCode1
Analogical Concept Memory for Architectures Implementing the Common Model of Cognition—0
Memorizing Complementation Network for Few-Shot Class-Incremental Learning—0
XCon: Learning with Experts for Fine-grained Category DiscoveryCode1
Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners—0
ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference TimeCode1
Malware Detection and Prevention using Artificial Intelligence Techniques—0
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
Discovering Latent Concepts Learned in BERT—0
A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches—0
Reaction Network Analysis of Metabolic Insulin Signaling—0
Rockafellian Relaxation and Stochastic Optimization under Perturbations—0
PaLM: Scaling Language Modeling with PathwaysCode2
A Closer Look at Rehearsal-Free Continual Learning—0
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations—0
Training Compute-Optimal Large Language ModelsCode6
Emergence of hierarchical reference systems in multi-agent communicationCode0
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications—0
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Learning Instance and Task-Aware Dynamic Kernels for Few Shot LearningCode1
Extract Free Dense Labels from CLIPCode1
Generative Pre-Trained Transformer for Design Concept Generation: An Exploration—0
Show:102550
← PrevPage 2 of 4Next →

No leaderboard results yet.