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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 626–650 of 796 papers

TitleStatusHype
The Importance of Socio-Cultural Differences for Annotating and Detecting the Affective States of Students—0
Using Scene Graph Context to Improve Image Generation—0
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning—0
Mapper Comparison with Wasserstein MetricsCode0
On the Dimensionality of Word EmbeddingCode0
SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction—0
Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation—0
New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity—0
PAC-learning in the presence of adversaries—0
Practical methods for graph two-sample testingCode0
Multi-scale variability in neuronal competition—0
Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extensions—0
Importance of Search and Evaluation Strategies in Neural Dialogue ModelingCode0
Depth with Nonlinearity Creates No Bad Local Minima in ResNets—0
Effective Parallelisation for Machine Learning—0
Agnostic Sample Compression Schemes for Regression—0
Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images—0
Learning Joint Wasserstein Auto-Encoders for Joint Distribution Matching—0
Fast Binary Functional Search on Graph—0
Discovering Features in Sr_14Cu_24O_41 Neutron Single Crystal Diffraction Data by Cluster Analysis—0
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction—0
Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification—0
A Tree-based Decoder for Neural Machine TranslationCode0
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study—0
The Impact of Automatic Pre-annotation in Clinical Note Data Element Extraction - the CLEAN Tool—0
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