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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 351–400 of 796 papers

TitleStatusHype
Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study over Open-ended Question Answering—0
Can Machine Learning Identify Governing Laws For Dynamics in Complex Engineered Systems ? : A Study in Chemical Engineering—0
Can visual information encoded in cortical columns be decoded from magnetoencephalography data in humans?—0
Can You Trust Your Pose? Confidence Estimation in Visual Localization—0
The (In)Effectiveness of Intermediate Task Training For Domain Adaptation and Cross-Lingual Transfer Learning—0
Characterizing the Effect of Sentence Context on Word Meanings: Mapping Brain to Behavior—0
Chromosomal rearrangements as a source of new gene formation in Drosophila yakuba—0
Cluster Activation Mapping with Applications to Medical Imaging—0
Clustering with Queries under Semi-Random Noise—0
Coalitional Manipulation for Schulze's Rule—0
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization—0
Complexity of Arithmetic in Warded Datalog+-—0
Compositionality and Capacity in Emergent Languages—0
Computational Complexity of Normalizing Constants for the Product of Determinantal Point Processes—0
Computational Concentration of Measure: Optimal Bounds, Reductions, and More—0
Computation with Sequences in a Model of the Brain—0
Conditional Noise-Contrastive Estimation of Unnormalised Models—0
Connecting Surrogate Safety Measures to Crash Probablity via Causal Probabilistic Time Series Prediction—0
Constant Regret, Generalized Mixability, and Mirror Descent—0
Sample Complexity of Learning Mixture of Sparse Linear Regressions—0
Sample Complexity of Learning Mixtures of Sparse Linear Regressions—0
Sample Complexity of Testing the Manifold Hypothesis—0
Sample Compression for Real-Valued Learners—0
SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction—0
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition—0
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic—0
Scalable Syntax-Aware Language Models Using Knowledge Distillation—0
SCALE SPACE FLOW WITH AUTOREGRESSIVE PRIORS—0
SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation—0
Searching for Carriers of the Diffuse Interstellar Bands Across Disciplines, using Natural Language Processing—0
Selectively Providing Reliance Calibration Cues With Reliance Prediction—0
Selective Particle Attention: Visual Feature-Based Attention in Deep Reinforcement Learning—0
Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs—0
Self-Interpretable Model with TransformationEquivariant Interpretation—0
SemEval-2019 Task 4: Hyperpartisan News Detection—0
Sentiment is all you need to win US Presidential elections—0
Shai: A large language model for asset management—0
Shaping the learning landscape in neural networks around wide flat minima—0
Long Story Short: Story-level Video Understanding from 20K Short Films—0
Significant Subgraph Mining with Multiple Testing Correction—0
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning—0
Simulations for Validation of Vision Systems—0
Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations—0
Single Pass Entrywise-Transformed Low Rank Approximation—0
Skeletonization and Reconstruction based on Graph Morphological Transformations—0
Slices of Attention in Asynchronous Video Job Interviews—0
Spatial-temporal traffic modeling with a fusion graph reconstructed by tensor decomposition—0
Speech-Based Emotion Recognition: Feature Selection by Self-Adaptive Multi-Criteria Genetic Algorithm—0
SpeechGen: Unlocking the Generative Power of Speech Language Models with Prompts—0
Spiking Network Initialisation and Firing Rate Collapse—0
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