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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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Large Language Models are not Fair Evaluators

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Unveiling Relations in the Industry 4.0 Standards Landscape based on Knowledge Graph Embeddings

https://github.com/iaar-shanghai/crud_rag

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CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models

https://github.com/iaar-shanghai/datg

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Controlled Text Generation for Large Language Model with Dynamic Attribute Graphs

https://github.com/iaar-shanghai/pgrag

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Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learning

https://github.com/iaar-shanghai/saferag

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SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model

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GINGER: Grounded Information Nugget-Based Generation of Responses

https://github.com/iamgmujtaba/scholar_search

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ChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey

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Prometheus Chatbot: Knowledge Graph Collaborative Large Language Model for Computer Components Recommendation

https://github.com/ianhuang0630/aladdin

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Aladdin: Zero-Shot Hallucination of Stylized 3D Assets from Abstract Scene Descriptions

https://github.com/iankur/vqllm

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Residual vector quantization for KV cache compression in large language model

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Hypernetwork Knowledge Graph Embeddings

https://github.com/ibalazevic/TuckER

공식 코드

TuckER: Tensor Factorization for Knowledge Graph Completion

https://github.com/ibm-ecosystem-engineering/blended-rag

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Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based Retrievers

https://github.com/ibm-granite/granite-guardian

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Granite Guardian

https://github.com/ibm/clai

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https://github.com/ibm/data-prep-kit

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Data-Prep-Kit: getting your data ready for LLM application development

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Re2G: Retrieve, Rerank, Generate

https://github.com/ibm/mt-rag-benchmark

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MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems

https://github.com/ibm/sax4bpm

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How well can a large language model explain business processes as perceived by users?

https://github.com/ibndias/cipher

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CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher

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KGLM: Integrating Knowledge Graph Structure in Language Models for Link Prediction

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Developing Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography

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GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes

https://github.com/icip-cas/selfretrieval

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Self-Retrieval: End-to-End Information Retrieval with One Large Language Model

https://github.com/icpc2024-so/icpc-2024

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Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative Study

https://github.com/ict-bigdatalab/rc-rag

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Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting Framework

https://github.com/ict-bigdatalab/utility_judgments

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Are Large Language Models Good at Utility Judgments?

https://github.com/ictmldm/SCAPE

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Panoramic Interests: Stylistic-Content Aware Personalized Headline Generation

https://github.com/ictnlp/LevelRAG

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LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searchers

https://github.com/ictnlp/auto-rag

공식 코드

Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models

https://github.com/ictnlp/bayling

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BayLing 2: A Multilingual Large Language Model with Efficient Language Alignment

https://github.com/ictnlp/flexrag

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FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation

https://github.com/ictnlp/stream-omni

공식 코드

Stream-Omni: Simultaneous Multimodal Interactions with Large Language-Vision-Speech Model

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