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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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Emergence of Social Norms in Generative Agent Societies: Principles and Architecture

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Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models

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Zero-Shot Industrial Anomaly Segmentation with Image-Aware Prompt Generation

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ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs

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T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Mixed Large Language Model Signals for Science Question Answering

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Generalizing Visual Question Answering from Synthetic to Human-Written Questions via a Chain of QA with a Large Language Model

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Multi-aspect Knowledge Distillation with Large Language Model

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4bit-Quantization in Vector-Embedding for RAG

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Lightweight Relevance Grader in RAG

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Text2SQL is Not Enough: Unifying AI and Databases with TAG

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Large Language Model based Multi-Agents: A Survey of Progress and Challenges

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KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion

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Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Family

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Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Family

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CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation

https://github.com/tanchongmin/arc-challenge

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Large Language Model (LLM) as a System of Multiple Expert Agents: An Approach to solve the Abstraction and Reasoning Corpus (ARC) Challenge

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Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility Prediction

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

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TruthEval: A Dataset to Evaluate LLM Truthfulness and Reliability

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RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models

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ChatVis: Automating Scientific Visualization with a Large Language Model

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LEAM: A Prompt-only Large Language Model-enabled Antenna Modeling Method

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Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

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https://github.com/taugroup/thinktank

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ThinkTank: A Framework for Generalizing Domain-Specific AI Agent Systems into Universal Collaborative Intelligence Platforms

https://github.com/tayebiarasteh/radiorag

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RadioRAG: Factual large language models for enhanced diagnostics in radiology using online retrieval augmented generation

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