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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/google-research/multilingual-t5

공식 코드

mT5: A massively multilingual pre-trained text-to-text transformer

https://github.com/google-research/scenic/tree/main/scenic/projects/knowledge_visual_language

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REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory

https://github.com/google-research/scenic/tree/main/scenic/projects/verbs_in_action

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Verbs in Action: Improving verb understanding in video-language models

https://github.com/google-research/tapas

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TAPAS: Weakly Supervised Table Parsing via Pre-training

https://github.com/google/haloquest

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HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning

https://github.com/google/retrieval-qa-eval

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ReQA: An Evaluation for End-to-End Answer Retrieval Models

https://github.com/google/spiqa

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SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers

https://github.com/google/trax/tree/master/trax/models/reformer

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Reformer: The Efficient Transformer

https://github.com/google/video-localized-narratives

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Connecting Vision and Language with Video Localized Narratives

https://github.com/gorov/BookQA

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Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study

https://github.com/gouqi666/rast

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Diversify Question Generation with Retrieval-Augmented Style Transfer

https://github.com/gpantaz/probing-resamplers

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Lost in Space: Probing Fine-grained Spatial Understanding in Vision and Language Resamplers

https://github.com/gpantaz/vl_mamba

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Shaking Up VLMs: Comparing Transformers and Structured State Space Models for Vision & Language Modeling

https://github.com/graal-research/risc

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RISC: Generating Realistic Synthetic Bilingual Insurance Contract

https://github.com/gradslam/gradslam

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gradSLAM: Automagically differentiable SLAM

https://github.com/graphnet-team/graphnet

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GraphNeT: Graph neural networks for neutrino telescope event reconstruction

https://github.com/greenaiproject/ict4s22

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Data-Centric Green AI: An Exploratory Empirical Study

https://github.com/grill-lab/oat

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GRILLBot In Practice: Lessons and Tradeoffs Deploying Large Language Models for Adaptable Conversational Task Assistants

https://github.com/grill-lab/wote

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GRILLBot In Practice: Lessons and Tradeoffs Deploying Large Language Models for Adaptable Conversational Task Assistants

https://github.com/gsarti/it5

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IT5: Text-to-text Pretraining for Italian Language Understanding and Generation

https://github.com/gsh199449/heteroqa

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HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling

https://github.com/gsh199449/productqa

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Product-Aware Answer Generation in E-Commerce Question-Answering

https://github.com/gsidiropoulos/dense-retrieval-against-misspellings

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Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellings

https://github.com/gsidiropoulos/hybrid_retrieval_for_efficient_qa

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Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question Answering

https://github.com/gsidiropoulos/passage_retrieval_for_spoken_qa

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On the Impact of Speech Recognition Errors in Passage Retrieval for Spoken Question Answering

https://github.com/guangyans/sys2-llava

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Visual Agents as Fast and Slow Thinkers

https://github.com/guanjinquan/cxrtrek

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Interpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical Reasoning

https://github.com/guilhermemr04/scaling-zero-shot-retrieval

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No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval

https://github.com/guotong1988/Semantic-Tree-Search

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Revisiting Semantic Representation and Tree Search for Similar Question Retrieval

https://github.com/guotong1988/table2answer

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Table2answer: Read the database and answer without SQL

https://github.com/guoyang9/AdaVQA

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AdaVQA: Overcoming Language Priors with Adapted Margin Cosine Loss

https://github.com/guoyang9/class-imbalance-VQA

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Loss re-scaling VQA: Revisiting the LanguagePrior Problem from a Class-imbalance View

https://github.com/guoyang9/unifer

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A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA

https://github.com/guoyang9/unk-vqa

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UNK-VQA: A Dataset and a Probe into the Abstention Ability of Multi-modal Large Models

https://github.com/guoyang9/vqa-prior

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Quantifying and Alleviating the Language Prior Problem in Visual Question Answering

https://github.com/guruprasad93/flexiblemachinelearning

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Engineering flexible machine learning systems by traversing functionally-invariant paths

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