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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/amazon-science/neoqa

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NeoQA: Evidence-based Question Answering with Generated News Events

https://github.com/amazon-science/tree-of-traversals

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Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs

https://github.com/amazonqa/amazonqa

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AmazonQA: A Review-Based Question Answering Task

https://github.com/ameenali/xai_transformers

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XAI for Transformers: Better Explanations through Conservative Propagation

https://github.com/ameyagodbole/long-tail-likelihood-splits

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Benchmarking Long-tail Generalization with Likelihood Splits

https://github.com/amiroor/d3questiongenerationclevr

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D3: Data Diversity Design for Systematic Generalization in Visual Question Answering

https://github.com/amitakamath/calibrated-qa

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Selective Question Answering under Domain Shift

https://github.com/amounts-tidings/fact_learning

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Co-occurrence is not Factual Association in Language Models

https://github.com/amourwaltz/ualign

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UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models

https://github.com/amphionspace/SA-Eval

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Solla: Towards a Speech-Oriented LLM That Hears Acoustic Context

https://github.com/amsterdata/ragbooster

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Improving Retrieval-Augmented Large Language Models via Data Importance Learning

https://github.com/amzn/refuel-open-domain-qa

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Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction

https://github.com/anand-subu/m-qalm

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M-QALM: A Benchmark to Assess Clinical Reading Comprehension and Knowledge Recall in Large Language Models via Question Answering

https://github.com/anastasiakrith/llm-for-vwsd

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Language Models as Knowledge Bases for Visual Word Sense Disambiguation

https://github.com/anastasiakrith/multimodal-retrieval-for-vwsd

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Large Language Models and Multimodal Retrieval for Visual Word Sense Disambiguation

https://github.com/andersonstra/mukea

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MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question Answering

https://github.com/andreamad8/QDREN

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Question Dependent Recurrent Entity Network for Question Answering

https://github.com/andreasvc/litquest

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Results of a Single Blind Literary Taste Test with Short Anonymized Novel Fragments

https://github.com/andrew-cullen/doublebubble

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Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity

https://github.com/andrewevag/SemEval2025-Task8-TQA

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AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question Answering

https://github.com/andst/text_guided_cl

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Text-Guided Image Clustering

https://github.com/andychiangsh/pre-cofactv3

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Team Trifecta at Factify5WQA: Setting the Standard in Fact Verification with Fine-Tuning

https://github.com/andyz245/LanguageAgentTreeSearch

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Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

https://github.com/andyzoujm/representation-engineering

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Representation Engineering: A Top-Down Approach to AI Transparency

https://github.com/angelosps/delta

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Transformers in the Service of Description Logic-based Contexts

https://github.com/ankeshanand/blindfold-baselines-eqa

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Blindfold Baselines for Embodied QA

https://github.com/ankush9812/aviation-question-answer-pairs

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There is No Big Brother or Small Brother: Knowledge Infusion in Language Models for Link Prediction and Question Answering

https://github.com/ankush9812/knowledge-infusion-in-lm-for-qa

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There is No Big Brother or Small Brother: Knowledge Infusion in Language Models for Link Prediction and Question Answering

https://github.com/anni-zou/decker

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Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification

https://github.com/anon809/efsum

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Evidence-Focused Fact Summarization for Knowledge-Augmented Zero-Shot Question Answering

https://github.com/anonymous-author-iccv2019/sanity_checks

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What Do Adversarially Robust Models Look At?

https://github.com/anonymous1252022/exaq

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EXAQ: Exponent Aware Quantization For LLMs Acceleration

https://github.com/anonynlp/natlan

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NatLan: Native Language Prompting Facilitates Knowledge Elicitation Through Language Trigger Provision and Domain Trigger Retention

https://github.com/anranwu-richpo/dcqa

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DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding

https://github.com/anthonyhuo/sam-dam-for-compositional-reasoning

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Composition Vision-Language Understanding via Segment and Depth Anything Model

https://github.com/anthonywchen/AmbER-Sets

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Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP

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