SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–450 of 796 papers

TitleStatusHype
Prediction of Non-Linguistic Information of Spontaneous Speech from the Prosodic Annotation: Evaluation of the X-JToBI system—0
Pretrained Diffusion Models for Unified Human Motion Synthesis—0
Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy—0
Private Learning Implies Online Learning: An Efficient Reduction—0
Private PAC learning implies finite Littlestone dimension—0
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons—0
Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models—0
Prompting Language Models for Linguistic Structure—0
Prompting Large Language Models with Speech Recognition Abilities—0
Proposing Plausible Answers for Open-ended Visual Question Answering—0
Quantification of Nematic Cell Polarity in Three-dimensional Tissues—0
Quantifying Complexity: An Object-Relations Approach to Complex Systems—0
Benchmarking Bayesian neural networks and evaluation metrics for regression tasks—0
Quantity beats quality for semantic segmentation of corrosion in images—0
Quantum versus Classical Generative Modelling in Finance—0
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization—0
Questioning the AI: Informing Design Practices for Explainable AI User Experiences—0
Radical pairs may play a role in microtubule reorganization—0
RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations—0
RangeAugment: Efficient Online Augmentation with Range Learning—0
Recognizing and Eliciting Weakly Single Crossing Profiles on Trees—0
Recursive Neural Networks Can Learn Logical Semantics—0
Reduced Label Complexity For Tight _2 Regression—0
Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form Text—0
Reflections on 30 Years of Language Resource Development and Sharing—0
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization—0
Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting—0
Reinforcement Learning reveals fundamental limits on the mixing of active particles—0
Reinforcement Learning using Guided Observability—0
Reinforcement Learning via AIXI Approximation—0
Relative Maximum Likelihood Updating of Ambiguous Beliefs—0
Repeatability of evolution on epistatic landscapes—0
Rethinking complex-valued deep neural networks for monaural speech enhancement—0
Rethinking Supervised Pre-training for Better Downstream Transferring—0
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm—0
Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity—0
Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation—0
Robust Linear Regression: Optimal Rates in Polynomial Time—0
Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation—0
Robust utility maximisation under proportional transaction costs for càdlàg price processes—0
Rotation-invariant clustering of neuronal responses in primary visual cortex—0
Rounding Sum-of-Squares Relaxations—0
Routing by spontaneous synchronization—0
RSI-Net: Two-Stream Deep Neural Network for Remote Sensing Imagesbased Semantic Segmentation—0
SAIL: Search-Augmented Instruction Learning—0
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise—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
Show:102550
← PrevPage 9 of 16Next →

No leaderboard results yet.