Answer Selection
47 papers with code • 6 benchmarks • 10 datasets
Answer Selection is the task of identifying the correct answer to a question from a pool of candidate answers. This task can be formulated as a classification or a ranking problem.
Source: Learning Analogy-Preserving Sentence Embeddings for Answer Selection
Most implemented papers
Recurrently Controlled Recurrent Networks
Recurrent neural networks (RNNs) such as long short-term memory and gated recurrent units are pivotal building blocks across a broad spectrum of sequence modeling problems.
BERTSel: Answer Selection with Pre-trained Models
we are the first to explore the performance of fine-tuning BERT for answer selection.
Sequential Attention with Keyword Mask Model for Community-based Question Answering
So the QA pairs capture features and information from both question text and answer text, interacting and improving vector representations iteratively through hops.
Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks
In this study, we propose a novel graph neural network called propagate-selector (PS), which propagates information over sentences to understand information that cannot be inferred when considering sentences in isolation.
A Gated Self-attention Memory Network for Answer Selection
Answer selection is an important research problem, with applications in many areas.
Neural Duplicate Question Detection without Labeled Training Data
We show that our proposed approaches are more effective in many cases because they can utilize larger amounts of unlabeled data from cQA forums.
Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering
Community question answering (CQA) gains increasing popularity in both academy and industry recently.
Review-guided Helpful Answer Identification in E-commerce
In this paper, we propose the Review-guided Answer Helpfulness Prediction (RAHP) model that not only considers the interactions between QA pairs but also investigates the opinion coherence between the answer and crowds' opinions reflected in the reviews, which is another important factor to identify helpful answers.
Contextualized Embeddings based Transformer Encoder for Sentence Similarity Modeling in Answer Selection Task
In this paper, we utilize contextualized word embeddings with the transformer encoder for sentence similarity modeling in the answer selection task.
MultiCQA: Zero-Shot Transfer of Self-Supervised Text Matching Models on a Massive Scale
We investigate the model performances on nine benchmarks of answer selection and question similarity tasks, and show that all 140 models transfer surprisingly well, where the large majority of models substantially outperforms common IR baselines.