https://github.com/hengrui-gu/pokemqa
공식 코드PokeMQA: Programmable knowledge editing for Multi-hop Question Answering
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
PokeMQA: Programmable knowledge editing for Multi-hop Question Answering
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Masking in Multi-hop QA: An Analysis of How Language Models Perform with Context Permutation
SituatedThinker: Grounding LLM Reasoning with Real-World through Situated Thinking
RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge Graphs
Focus, Merge, Rank: Improved Question Answering Based on Semi-structured Knowledge Bases
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs
Single and Multi-Hop Question-Answering Datasets for Reticular Chemistry with GPT-4-Turbo
EfficientRAG: Efficient Retriever for Multi-Hop Question Answering
Self-prompted Chain-of-Thought on Large Language Models for Open-domain Multi-hop Reasoning
Answering Questions by Meta-Reasoning over Multiple Chains of Thought
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
MINTQA: A Multi-Hop Question Answering Benchmark for Evaluating LLMs on New and Tail Knowledge
KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing
GNN2R: Weakly-Supervised Rationale-Providing Question Answering over Knowledge Graphs
KITLM: Domain-Specific Knowledge InTegration into Language Models for Question Answering
Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning
MuSiQue: Multihop Questions via Single-hop Question Composition
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering
Unsupervised Multi-hop Question Answering by Question Generation
Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration
Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering
Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.