https://github.com/2282588541a/hirag
공식 코드Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering
Papers with Code 아카이브
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/ABi-dot/Kedkg
공식 코드Knowledge Editing with Dynamic Knowledge Graphs for Multi-Hop Question Answering
https://github.com/AgnostiqHQ/multi-agent-llm
공식 코드Iteration of Thought: Leveraging Inner Dialogue for Autonomous Large Language Model Reasoning
https://github.com/Alab-NII/2wikimultihop
공식 코드Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps
https://github.com/DevinJake/NS-CQA
공식 코드Less is More: Data-Efficient Complex Question Answering over Knowledge Bases
https://github.com/HITsz-TMG/SKURG
공식 코드https://github.com/HLR/SRLGRN
공식 코드https://github.com/IAAR-Shanghai/Meta-Chunking
공식 코드Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception
https://github.com/INK-USC/NExT
공식 코드https://github.com/Javihaus/Optimizing-AI-Reasoning
공식 코드Optimizing AI Reasoning: A Hamiltonian Dynamics Approach to Multi-Hop Question Answering
https://github.com/PlusLabNLP/Re-ReST
공식 코드Re-ReST: Reflection-Reinforced Self-Training for Language Agents
https://github.com/StonyBrookNLP/multee
공식 코드Repurposing Entailment for Multi-Hop Question Answering Tasks
https://github.com/THUDM/CogQA
공식 코드Cognitive Graph for Multi-Hop Reading Comprehension at Scale
https://github.com/agent-husky/husky-v1
공식 코드Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning
https://github.com/ai-systems/hybrid_autoregressive_inference
공식 코드Hybrid Autoregressive Inference for Scalable Multi-hop Explanation Regeneration
https://github.com/airi-institute/arigraph
공식 코드AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents
https://github.com/alab-nii/multi-hop-analysis
공식 코드Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering
https://github.com/albert-jin/rce-kgqa
공식 코드https://github.com/alibaba-nlp/masksearch
공식 코드MASKSEARCH: A Universal Pre-Training Framework to Enhance Agentic Search Capability
https://github.com/allen-li1231/treehop-rag
공식 코드TreeHop: Generate and Filter Next Query Embeddings Efficiently for Multi-hop Question Answering
https://github.com/allenai/missing-fact
공식 코드What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering
https://github.com/allenai/qasc
공식 코드QASC: A Dataset for Question Answering via Sentence Composition
https://github.com/aloriosa/gemformer
공식 코드Uncertainty Guided Global Memory Improves Multi-Hop Question Answering
https://github.com/amounts-tidings/fact_learning
공식 코드https://github.com/arthur-heng/nlgraph
공식 코드Can Language Models Solve Graph Problems in Natural Language?
https://github.com/bai-lab/kg-retriever
공식 코드KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models
https://github.com/bcdnlp/structure-qa
공식 코드Leveraging Structured Information for Explainable Multi-hop Question Answering and Reasoning
https://github.com/bvanaken/visbert
공식 코드https://github.com/canghongjian/beam_retriever
공식 코드https://github.com/clinicalml/teaching-to-understand-ai
공식 코드https://github.com/dmis-lab/compact
공식 코드CompAct: Compressing Retrieved Documents Actively for Question Answering
https://github.com/ecnu-text-computing/dcs
공식 코드https://github.com/facebookresearch/concurrentqa
공식 코드Reasoning over Public and Private Data in Retrieval-Based Systems
https://github.com/freedomintelligence/reasoningnlp
공식 코드https://github.com/gsidiropoulos/hybrid_retrieval_for_efficient_qa
공식 코드Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question Answering
https://github.com/gy915/dr3
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.