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Knowledge Graph Completion

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하위 태스크: 4
평가표: 7
보존된 평가 기록: 17

Knowledge graphs $G$ are represented as a collection of triples $\\{(h, r, t)\\}\subseteq E\times R\times E$, where $E$ and $R$ are the entity set and relation set. The task of Knowledge Graph Completion is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.

Source: One-Shot Relational Learning for Knowledge Graphs

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

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Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents

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MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

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Large Language Models Enable Few-Shot Clustering

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DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

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Neural Compositional Rule Learning for Knowledge Graph Reasoning

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Attacks on Third-Party APIs of Large Language Models

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PatentLMM: Large Multimodal Model for Generating Descriptions for Patent Figures

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Bias in Knowledge Graphs -- an Empirical Study with Movie Recommendation and Different Language Editions of DBpedia

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VirusT5: Harnessing Large Language Models to Predicting SARS-CoV-2 Evolution

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A Toolkit for Generating Code Knowledge Graphs

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Unifying Multimodal Large Language Model Capabilities and Modalities via Model Merging

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WalledEval: A Comprehensive Safety Evaluation Toolkit for Large Language Models

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G2S: A General-to-Specific Learning Framework for Temporal Knowledge Graph Forecasting with Large Language Models

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Diabetica: Adapting Large Language Model to Enhance Multiple Medical Tasks in Diabetes Care and Management

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Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models

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TracLLM: A Generic Framework for Attributing Long Context LLMs

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Explainable Fake News Detection With Large Language Model via Defense Among Competing Wisdom

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Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion

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ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation

https://github.com/wangjunchi/llmseg

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