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 126–150 of 158 papers

TitleStatusHype
SECURE: Semantics-aware Embodied Conversation under Unawareness for Lifelong Robot Learning—0
Sequential Local Learning for Latent Graphical Models—0
Zero-Shot Learning by Generating Pseudo Feature Representations—0
Situational Grounding within Multimodal Simulations—0
Weakly Supervised Open-Vocabulary Object Detection—0
Sketch-Plan-Generalize: Learning and Planning with Neuro-Symbolic Programmatic Representations for Inductive Spatial Concepts—0
Smoothed Bernstein Online Aggregation for Day-Ahead Electricity Demand Forecasting—0
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications—0
Statistical QoS Provisioning Analysis and Performance Optimization in xURLLC-enabled Massive MU-MIMO Networks: A Stochastic Network Calculus Perspective—0
Strategy Synthesis in Markov Decision Processes Under Limited Sampling Access—0
Structure Matters: Towards Generating Transferable Adversarial Images—0
What happens when generative AI models train recursively on each others' generated outputs?—0
Surprisal Driven k-NN for Robust and Interpretable Nonparametric Learning—0
Word reuse and combination support efficient communication of emerging concepts—0
Analogical Concept Memory for Architectures Implementing the Common Model of Cognition—0
Discovering Latent Concepts Learned in BERT—0
DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter—0
Direct and indirect transactions and requirements—0
DRPT: Disentangled and Recurrent Prompt Tuning for Compositional Zero-Shot Learning—0
Dual-View Data Hallucination with Semantic Relation Guidance for Few-Shot Image Recognition—0
Dialog Policy Learning for Joint Clarification and Active Learning Queries—0
Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners—0
Efficient Transmission of Radiomaps via Physics-Enhanced Semantic Communications—0
A Closer Look at Rehearsal-Free Continual Learning—0
Enhancing Balanced Graph Edge Partition with Effective Local Search—0
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