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 1–50 of 158 papers

TitleStatusHype
Training Compute-Optimal Large Language ModelsCode6
Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing CommunityCode3
Is CLIP the main roadblock for fine-grained open-world perception?Code2
Attention Calibration for Disentangled Text-to-Image PersonalizationCode2
SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary ConstraintsCode2
PaLM: Scaling Language Modeling with PathwaysCode2
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic SegmentationCode1
PersonaMagic: Stage-Regulated High-Fidelity Face Customization with Tandem EquilibriumCode1
Grounding Descriptions in Images informs Zero-Shot Visual RecognitionCode1
SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained ModelsCode1
Happy: A Debiased Learning Framework for Continual Generalized Category DiscoveryCode1
A Language Model's Guide Through Latent SpaceCode1
Online Task-Free Continual Generative and Discriminative Learning via Dynamic Cluster MemoryCode1
Language-Informed Visual Concept LearningCode1
DreamCreature: Crafting Photorealistic Virtual Creatures from ImaginationCode1
Towards Open-Ended Visual Recognition with Large Language ModelCode1
OV-VG: A Benchmark for Open-Vocabulary Visual GroundingCode1
Link-Context Learning for Multimodal LLMsCode1
CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent MaskingCode1
Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class DiscoveryCode1
IFSeg: Image-free Semantic Segmentation via Vision-Language ModelCode1
LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object DetectionCode1
Few-Shot Class-Incremental Learning via Class-Aware Bilateral DistillationCode1
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual LearningCode1
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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