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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 151–200 of 796 papers

TitleStatusHype
Evaluation of the Synthetic Electronic Health Records—0
Legal Case Document Summarization: Extractive and Abstractive Methods and their EvaluationCode2
OpenCQA: Open-ended Question Answering with ChartsCode1
Double Bubble, Toil and Trouble: Enhancing Certified Robustness through TransitivityCode0
KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document UnderstandingCode0
Are Representations Built from the Ground Up? An Empirical Examination of Local Composition in Language ModelsCode0
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text—0
Nanoscopic distribution of VAChT and VGLUT3 in striatal cholinergic varicosities suggests colocalization and segregation of the two transporters in synaptic vesicles—0
Connecting Surrogate Safety Measures to Crash Probablity via Causal Probabilistic Time Series Prediction—0
The (In)Effectiveness of Intermediate Task Training For Domain Adaptation and Cross-Lingual Transfer Learning—0
Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in BanditsCode0
Linearly Mapping from Image to Text SpaceCode1
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-TrainingCode1
Sentiment is all you need to win US Presidential elections—0
Interpreting the Mechanism of Synergism for Drug Combinations Using Attention-Based Hierarchical Graph Pooling—0
Gradient Norm Minimization of Nesterov Acceleration: o(1/k^3)—0
Structured Knowledge Grounding for Question Answering—0
On the Convergence of Monte Carlo UCB for Random-Length Episodic MDPs—0
Near-Optimal Φ-Regret Learning in Extensive-Form Games—0
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data—0
Semantic Communications with Discrete-time Analog Transmission: A PAPR PerspectiveCode1
Benchmarking Compositionality with Formal LanguagesCode1
Action Recognition based on Cross-Situational Action-object StatisticsCode0
Deep Machine Learning Reconstructing Lattice Topology with Strong Thermal Fluctuations—0
Understanding Masked Image Modeling via Learning Occlusion Invariant Feature—0
Neuro-symbolic computing with spiking neural networksCode1
Homomorphism Autoencoder -- Learning Group Structured Representations from Observed TransitionsCode1
Leveraging Natural Supervision for Language Representation Learning and GenerationCode1
Online Lewis Weight Sampling—0
Online Prediction in Sub-linear Space—0
CoSCL: Cooperation of Small Continual Learners is Stronger than a Big OneCode1
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG—0
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm—0
Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic—0
The Parallelism Tradeoff: Limitations of Log-Precision Transformers—0
Incorporating Centering Theory into Neural Coreference ResolutionCode0
Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting—0
Optimizing Video Prediction via Video Frame InterpolationCode1
Tackling Spoofing-Aware Speaker Verification with Multi-Model Fusion—0
Learning to Rank Rationales for Explainable RecommendationCode0
When Does Adaptivity Help for Quantum State Learning?—0
A general approximation lower bound in L^p norm, with applications to feed-forward neural networks—0
Clustering with Queries under Semi-Random Noise—0
Learning to generate imaginary tasks for improving generalization in meta-learning—0
Benchmarking Bayesian neural networks and evaluation metrics for regression tasks—0
Scaling laws in global corporations as a benchmarking approach to assess environmental performance—0
Is Mapping Necessary for Realistic PointGoal Navigation?Code1
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs—0
Reflections on 30 Years of Language Resource Development and Sharing—0
Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random VariablesCode1
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