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Multi-hop Question Answering
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wenhuchen/HybridQA
공식 코드HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data
https://github.com/wwxu21/AMR-SG
공식 코드https://github.com/xsc1234/search-in-the-chain
공식 코드https://github.com/yicheng-w/CommonSenseMultiHopQA
공식 코드Commonsense for Generative Multi-Hop Question Answering Tasks
https://github.com/yinzhangyue/c2fm
공식 코드https://github.com/yinzhangyue/smoothing-r3
공식 코드https://github.com/yuwfan/HGN
공식 코드https://github.com/zchuz/sigir-mhqa
공식 코드Self-Critique Guided Iterative Reasoning for Multi-hop Question Answering
https://github.com/zh1yushen/hopweaver
공식 코드HopWeaver: Synthesizing Authentic Multi-Hop Questions Across Text Corpora
https://github.com/zuucan/needleinahaystack-plus
공식 코드LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
https://worksheets.codalab.org/worksheets/0xf215deb05edf44a2ac353c711f52a25f
공식 코드QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/Bodoral/MuSiQue_replication
MuSiQue: Multihop Questions via Single-hop Question Composition
https://github.com/CMSC470-Team/Model
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/HaochenLiu2000/QAP
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/Samyu0304/thought-propagation
Can Language Models Solve Graph Problems in Natural Language?
https://github.com/ShaoaAllen/CogQA
Cognitive Graph for Multi-Hop Reading Comprehension at Scale
https://github.com/ShayekhBinIslam/openrag
https://github.com/a414351664/NarrativeQA
Commonsense for Generative Multi-Hop Question Answering Tasks
https://github.com/circlemind-ai/fast-graphrag
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
https://github.com/codelion/optillm/blob/main/optillm/leap.py
https://github.com/hi-archers/stableke
MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
https://github.com/mangopy/direct-rag-learning
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
https://github.com/qirui-chen/MultiHop-EgoQA
https://github.com/ruc-nlpir/flashrag
Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy
https://github.com/rucaibox/safe
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/soujanyarbhat/aNswER_multirc
Repurposing Entailment for Multi-Hop Question Answering Tasks
https://github.com/tobias-opsahl/fact-or-fiction
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/varunchaudharycs/aNswER_multirc
Repurposing Entailment for Multi-Hop Question Answering Tasks
https://github.com/varunchaudharycs/multi_rc
Repurposing Entailment for Multi-Hop Question Answering Tasks
https://github.com/zeaver/multifactor
QA4QG: Using Question Answering to Constrain Multi-Hop Question Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.