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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 101–150 of 796 papers

TitleStatusHype
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over ModulesCode1
Learning to Cluster Faces on an Affinity GraphCode1
Training language models to summarize narratives improves brain alignmentCode1
Benchmarking Compositionality with Formal LanguagesCode1
Coresets for Data-efficient Training of Machine Learning ModelsCode1
Leveraging Natural Supervision for Language Representation Learning and GenerationCode1
Bridging Cost-sensitive and Neyman-Pearson Paradigms for Asymmetric Binary ClassificationCode0
BoXHED: Boosted eXact Hazard Estimator with Dynamic covariatesCode0
On the Impossibility of Global Convergence in Multi-Loss OptimizationCode0
On the Benefit of Combining Neural, Statistical and External Features for Fake News IdentificationCode0
Obtaining Adjustable Regularization for Free via Iterate AveragingCode0
On the Dimensionality of Word EmbeddingCode0
Benchmarking Model-Based Reinforcement LearningCode0
A Monte Carlo AIXI ApproximationCode0
Near-optimal multiple testing in Bayesian linear models with finite-sample FDR controlCode0
Nonparametric estimation of continuous DPPs with kernel methodsCode0
Modularity maximisation for graphonsCode0
Monolingual or Multilingual Instruction Tuning: Which Makes a Better AlpacaCode0
Model Selection in Bayesian Neural Networks via Horseshoe PriorsCode0
Action Recognition based on Cross-Situational Action-object StatisticsCode0
AutoRL Hyperparameter LandscapesCode0
2D-Shapley: A Framework for Fragmented Data ValuationCode0
A Unified Theory of Diversity in Ensemble LearningCode0
Augmenting Neural Networks with First-order LogicCode0
Learning Representations for Time Series ClusteringCode0
Learning Theory for Distribution RegressionCode0
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural NetworksCode0
Learned Sorted Table Search and Static Indexes in Small Model SpaceCode0
A Tree-based Decoder for Neural Machine TranslationCode0
Learning to Rank Rationales for Explainable RecommendationCode0
Mapper Comparison with Wasserstein MetricsCode0
KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document UnderstandingCode0
Is Deeper Better only when Shallow is Good?Code0
Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsCode0
Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in BanditsCode0
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural NetworksCode0
Incorporating Centering Theory into Neural Coreference ResolutionCode0
Langevin DQNCode0
A Revenue Function for Comparison-Based Hierarchical ClusteringCode0
Are Representations Built from the Ground Up? An Empirical Examination of Local Composition in Language ModelsCode0
Implicit Regularization in Deep Learning May Not Be Explainable by NormsCode0
Adversaries with Limited Information in the Friedkin--Johnsen ModelCode0
How intelligence can change the course of evolutionCode0
Importance of Search and Evaluation Strategies in Neural Dialogue ModelingCode0
Geolocating Political Events in TextCode0
An Open-Source Framework for Adaptive Traffic Signal ControlCode0
A Nonlinear Observability Analysis of Ambient Wind Estimation with Uncalibrated Sensors, Inspired by Insect Neural EncodingCode0
A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition TasksCode0
Finding Physical Adversarial Examples for Autonomous Driving with Fast and Differentiable Image CompositingCode0
Full-Capacity Unitary Recurrent Neural NetworksCode0
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