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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/AkariAsai/XORQA

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XOR QA: Cross-lingual Open-Retrieval Question Answering

https://github.com/AkariAsai/learning_to_retrieve_reasoning_paths

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Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering

https://github.com/AkariAsai/logic_guided_qa

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Logic-Guided Data Augmentation and Regularization for Consistent Question Answering

https://github.com/AkariAsai/self-rag

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Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

https://github.com/Akutagawa1998/LazyBench

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Difficult Task Yes but Simple Task No: Unveiling the Laziness in Multimodal LLMs

https://github.com/AlCorreia/FABIR

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A Fully Attention-Based Information Retriever

https://github.com/Alab-NII/2wikimultihop

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Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

https://github.com/AlexJJJChen/Climate-Zoo

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Vision-Language Models Meet Meteorology: Developing Models for Extreme Weather Events Detection with Heatmaps

https://github.com/Alexgichamba/itu_qna_challenge

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ColBERT Retrieval and Ensemble Response Scoring for Language Model Question Answering

https://github.com/Alibaba-NLP/ViDoRAG

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ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents

https://github.com/AmeyHengle/multilingual-needle-in-a-haystack

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Multilingual Needle in a Haystack: Investigating Long-Context Behavior of Multilingual Large Language Models

https://github.com/AndreasMadsen/llm-introspection

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Are self-explanations from Large Language Models faithful?

https://github.com/AndreasMadsen/nlp-roar-interpretability

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Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining

https://github.com/Anirudh-Phukan/verifiability-granular

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Peering into the Mind of Language Models: An Approach for Attribution in Contextual Question Answering

https://github.com/Applied-Machine-Learning-Lab/AMAR

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Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation

https://github.com/AskNowQA/DeepShallowParsingQA

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Distantly Supervised Question Parsing

https://github.com/AskNowQA/EARL

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EARL: Joint Entity and Relation Linking for Question Answering over Knowledge Graphs

https://github.com/AskNowQA/KrantikariQA

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Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs

https://github.com/AskNowQA/VANiLLa

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VANiLLa : Verbalized Answers in Natural Language at Large Scale

https://github.com/Aunsiels/CSK

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Commonsense Properties from Query Logs and Question Answering Forums

https://github.com/BangLiu/ArticlePairMatching

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Matching Article Pairs with Graphical Decomposition and Convolutions

https://github.com/Ber666/ToolkenGPT

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ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

https://github.com/Bhavik-Ardeshna/Question-Answering-for-Low-Resource-Languages

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Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages

https://github.com/BierOne/VQA-AttReg

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Answer Questions with Right Image Regions: A Visual Attention Regularization Approach

https://github.com/BoXHED/BoXHED1.0

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BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates

https://github.com/BoulderDS/evaluating-human-rationales

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Evaluating and Characterizing Human Rationales

https://github.com/Brain-Cog-Lab/IEMF

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Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligence

https://github.com/Bravo5542/TJSTG

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Target-Aware Spatio-Temporal Reasoning via Answering Questions in Dynamics Audio-Visual Scenarios

https://github.com/BrianPulfer/fsaa

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Task-Agnostic Attacks Against Vision Foundation Models

https://github.com/Buzz-Beater/EgoTaskQA

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EgoTaskQA: Understanding Human Tasks in Egocentric Videos

https://github.com/C4AI/Pira

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Pirá: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean

https://github.com/CLARIN-PL/PUGG

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Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction

https://github.com/CMFiltenborg/lingually_constrained_tracking

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Siamese Tracking with Lingual Object Constraints

https://github.com/CONE-MT/multilingual_reasoning

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Could Thinking Multilingually Empower LLM Reasoning?

https://github.com/CYandYue/Dentist

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A Unified Hallucination Mitigation Framework for Large Vision-Language Models

https://github.com/CZWin32768/XLM-Align

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Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.