Answer Generation
27 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Answer Generation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
CICERO
Most implemented papers
Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering
While question answering (QA) with neural network, i. e. neural QA, has achieved promising results in recent years, lacking of large scale real-word QA dataset is still a challenge for developing and evaluating neural QA system.
Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus
bangliu/ACS-QG
•
•
In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.
LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering
We show that LRTA makes a step towards truly understanding the question while the state-of-the-art model tends to learn superficial correlations from the training data.
It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Books
WorkInTheDark/FairytaleQA_QAG_System
•
•
Existing question answering (QA) techniques are created mainly to answer questions asked by humans.
R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering
Second, we propose a novel method that jointly trains the Ranker along with an answer-generation Reader model, based on reinforcement learning.
Product-Aware Answer Generation in E-Commerce Question-Answering
In this paper, we propose the task of product-aware answer generation, which tends to generate an accurate and complete answer from large-scale unlabeled e-commerce reviews and product attributes.
Review-Driven Answer Generation for Product-Related Questions in E-Commerce
WHUIR/RAGE
•
•
Then, we devise a mechanism to identify the relevant information from the noise-prone review snippets and incorporate this information to guide the answer generation.
AmazonQA: A Review-Based Question Answering Task
Observing that many questions can be answered based upon the available product reviews, we propose the task of review-based QA.
Answering Naturally: Factoid to Full length Answer Generation
kolk/AnsweringNaturally
•
•
WS 2019
A reading comprehension system extracts a span of text, comprising of named entities, dates, small phrases, etc., which serve as the answer to a given question.
VD-BERT: A Unified Vision and Dialog Transformer with BERT
salesforce/VD-BERT
•
•
EMNLP 2020
By contrast, in this work, we propose VD-BERT, a simple yet effective framework of unified vision-dialog Transformer that leverages the pretrained BERT language models for Visual Dialog tasks.
