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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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FedJudge: Federated Legal Large Language Model

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Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias

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G-Refer: Graph Retrieval-Augmented Large Language Model for Explainable Recommendation

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A Semantic Partitioning Method for Large-Scale Training of Knowledge Graph Embeddings

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Distantly-Supervised Joint Extraction with Noise-Robust Learning

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GreenKGC: A Lightweight Knowledge Graph Completion Method

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LMEye: An Interactive Perception Network for Large Language Models

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Co-Learning: Code Learning for Multi-Agent Reinforcement Collaborative Framework with Conversational Natural Language Interfaces

https://github.com/yur7nd/ptss

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Repurposing Knowledge Graph Embeddings for Triple Representation via Weak Supervision

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LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large Contexts

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V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization

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LLM-Assisted Multi-Teacher Continual Learning for Visual Question Answering in Robotic Surgery

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Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

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Neuro-Symbolic Query Compiler

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PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation

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TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning

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Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations

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Fine-tuning a Large Language Model for Automating Computational Fluid Dynamics Simulations

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Sentinel: Decoding Context Utilization via Attention Probing for Efficient LLM Context Compression

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PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection

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MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model

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PeriGuru: A Peripheral Robotic Mobile App Operation Assistant based on GUI Image Understanding and Prompting with LLM

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CoIN: A Benchmark of Continual Instruction tuNing for Multimodel Large Language Model

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ShizishanGPT: An Agricultural Large Language Model Integrating Tools and Resources

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Critique-out-Loud Reward Models

https://github.com/zayne-sprague/deductive_additivity_for_planning_of_natural_language_proofs

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Deductive Additivity for Planning of Natural Language Proofs

https://github.com/zcaicaros/pmc

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Planning with Multi-Constraints via Collaborative Language Agents

https://github.com/zcccccz/causalwalk

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Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment

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InvAgent: A Large Language Model based Multi-Agent System for Inventory Management in Supply Chains

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RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict

https://github.com/zengrh3/StructuralMemory

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On the Structural Memory of LLM Agents

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