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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 21–30 of 796 papers

TitleStatusHype
Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous TuningCode1
mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language ModelsCode1
When should we prefer Decision Transformers for Offline Reinforcement Learning?Code1
Improving Implicit Feedback-Based Recommendation through Multi-Behavior AlignmentCode1
Masked Structural Growth for 2x Faster Language Model Pre-trainingCode1
Time Series Contrastive Learning with Information-Aware AugmentationsCode1
SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained ModelCode1
Cross-modal Contrastive Learning for Multimodal Fake News DetectionCode1
Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the LeastCode1
Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question AnsweringCode1
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