SOTAVerified

Temporal Sequences

This task asks models to answer questions about which times certain events could have occurred.

Source: BIG-bench

Image source: BIG-bench

Papers

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Showing 176–200 of 200 papers

TitleStatusHype
Global and Local Interpretability for Cardiac MRI Classification—0
HandDiffuse: Generative Controllers for Two-Hand Interactions via Diffusion Models—0
Handwriting styles: benchmarks and evaluation metrics—0
Hierarchical recurrent neural network for skeleton based action recognition—0
Hunyuan-GameCraft: High-dynamic Interactive Game Video Generation with Hybrid History Condition—0
Ice hockey player identification via transformers and weakly supervised learning—0
Improving Trajectory Prediction in Dynamic Multi-Agent Environment by Dropping Waypoints—0
IMSSA: Deploying modern state-space models on memristive in-memory compute hardware—0
Interpretable Neural Temporal Point Processes for Modelling Electronic Health Records—0
Inverse RL Scene Dynamics Learning for Nonlinear Predictive Control in Autonomous Vehicles—0
Investigating current-based and gating approaches for accurate and energy-efficient spiking recurrent neural networks—0
Keyframing the Future: Discovering Temporal Hierarchy with Keyframe-Inpainter Prediction—0
Learning Finite Linear Temporal Logic Specifications with a Specialized Neural Operator—0
Learning Object Semantic Similarity with Self-Supervision—0
Learning Scene Dynamics from Point Cloud Sequences—0
Learning to combine top-down context and feed-forward representations under ambiguity with apical and basal dendrites—0
Leveraging Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations—0
LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure Cooperation—0
LLM4FTS: Enhancing Large Language Models for Financial Time Series Prediction—0
MarineFormer: A Spatio-Temporal Attention Model for USV Navigation in Dynamic Marine Environments—0
metricDTW: local distance metric learning in Dynamic Time Warping—0
Mitigating LLM Hallucinations via Conformal Abstention—0
Modeling Time-Series and Spatial Data for Recommendations and Other Applications—0
Multi-instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation—0
Multi-Instance Dynamic Ordinal Random Fields for Weakly-supervised Facial Behavior Analysis—0
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