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Question Answering

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하위 태스크: 19
평가표: 153
보존된 평가 기록: 1,781

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Cadene/block.bootstrap.pytorch

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BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

https://github.com/Caojunxu/AC-FPN

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Attention-guided Context Feature Pyramid Network for Object Detection

https://github.com/Chandrahasd/OKGIT

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OKGIT: Open Knowledge Graph Link Prediction with Implicit Types

https://github.com/ChenRocks/Distill-BERT-Textgen

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Distilling Knowledge Learned in BERT for Text Generation

https://github.com/ChenRocks/UNITER

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UNITER: UNiversal Image-TExt Representation Learning

https://github.com/China-UK-ZSL/ZS-F-VQA

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Zero-shot Visual Question Answering using Knowledge Graph

https://github.com/Cloudy1225/HTAG

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Multi-Scale Heterogeneous Text-Attributed Graph Datasets From Diverse Domains

https://github.com/CogComp/PABI

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Foreseeing the Benefits of Incidental Supervision

https://github.com/CogComp/QuASE

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QuASE: Question-Answer Driven Sentence Encoding

https://github.com/CogComp/qaeval-experiments

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Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary

https://github.com/Cold-Winter/vqs

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VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation

https://github.com/CrossmodalGroup/SSL-VQA

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Overcoming Language Priors with Self-supervised Learning for Visual Question Answering

https://github.com/Cyanogenoid/perm-optim

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Learning Representations of Sets through Optimized Permutations

https://github.com/DAVID-NGUYEN-S16/SemViQA

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SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking

https://github.com/DS3Lab/WordScape

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WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data

https://github.com/DataScienceUIBK/PlausibleQA

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Wrong Answers Can Also Be Useful: PlausibleQA -- A Large-Scale QA Dataset with Answer Plausibility Scores

https://github.com/DataScienceUIBK/Rankify

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Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation

https://github.com/DataScienceUIBK/TempAmbiQA

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Detecting Temporal Ambiguity in Questions

https://github.com/Deanplayerljx/tab-vcr

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TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines

https://github.com/DecstionBack/AAAI_2020_CommonsenseQA

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Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering

https://github.com/DeepLearnXMU/QGC

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Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs

https://github.com/DelTA-Lab-IITK/CCM-WACV

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Robust Explanations for Visual Question Answering

https://github.com/Depth2World/VLADBench

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Fine-Grained Evaluation of Large Vision-Language Models in Autonomous Driving

https://github.com/DevSinghSachan/emdr2

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End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering

https://github.com/DevSinghSachan/unsupervised-passage-reranking

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Improving Passage Retrieval with Zero-Shot Question Generation

https://github.com/DevinJake/MARL

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Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning

https://github.com/DevinJake/MRL-CQA

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Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning

https://github.com/DevinJake/NS-CQA

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Less is More: Data-Efficient Complex Question Answering over Knowledge Bases

https://github.com/DigitalPhonetics/reading-comprehension

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Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

https://github.com/DragonLiu1995/MUSIC-AVQA-v2.0

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Tackling Data Bias in MUSIC-AVQA: Crafting a Balanced Dataset for Unbiased Question-Answering

https://github.com/DreadPiratePsyopus/Fine_Grained_Clf

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Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features

https://github.com/DriveVLA/OpenDriveVLA

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OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model

https://github.com/EchoDreamer/Q-KGR

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Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering

https://github.com/EdisonNi-hku/Robust_Evidence_Based_QA

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Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering

https://github.com/EdisonNi-hku/when-does-mtl-work

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When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP

https://github.com/EmergenceAI/dartboard

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Better RAG using Relevant Information Gain

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