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Open-Ended Question Answering

Open-ended questions are defined as those that simply pose the question, without imposing any constraints on the format of the response. This distinguishes them from questions with a predetermined answer format.

Papers

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Showing 451–475 of 796 papers

TitleStatusHype
Obtaining Adjustable Regularization for Free via Iterate AveragingCode0
RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations—0
Transferring Inter-Class Correlation—0
Efficient Integration of Multi-channel Information for Speaker-independent Speech Separation—0
Quantum versus Classical Generative Modelling in Finance—0
UNIPoint: Universally Approximating Point Processes Intensities—0
Characterizing the Effect of Sentence Context on Word Meanings: Mapping Brain to Behavior—0
Approximately Optimal Binning for the Piecewise Constant Approximation of the Normalized Unexplained Variance (nUV) Dissimilarity Measure—0
MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint—0
On the Convergence of Reinforcement Learning with Monte Carlo Exploring Starts—0
Discovering Reinforcement Learning AlgorithmsCode1
Learn to Propagate Reliably on Noisy Affinity Graphs—0
How Retroactivity Affects the Behavior of Incoherent Feed-Forward Loops—0
Attack of the Tails: Yes, You Really Can Backdoor Federated LearningCode1
Stochastic Stein DiscrepanciesCode0
Knowledge Distillation Beyond Model Compression—0
Compositionality and Capacity in Emergent Languages—0
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over ModulesCode1
Robust Linear Regression: Optimal Rates in Polynomial Time—0
BoXHED: Boosted eXact Hazard Estimator with Dynamic covariatesCode0
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation—0
Graph Neural Network Based Coarse-Grained Mapping PredictionCode1
On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures—0
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks—0
A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition TasksCode0
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