https://github.com/lavis-nlp/irt2
공식 코드IRT2: Inductive Linking and Ranking in Knowledge Graphs of Varying Scale
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A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
IRT2: Inductive Linking and Ranking in Knowledge Graphs of Varying Scale
Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks
NESTLE: a No-Code Tool for Statistical Analysis of Legal Corpus
Knowledgeable-r1: Policy Optimization for Knowledge Exploration in Retrieval-Augmented Generation
ECoRAG: Evidentiality-guided Compression for Long Context RAG
Large Language Models as Realistic Microservice Trace Generators
Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing
Meaning Typed Prompting: A Technique for Efficient, Reliable Structured Output Generation
One for All: Towards Training One Graph Model for All Classification Tasks
wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech
MacRAG: Compress, Slice, and Scale-up for Multi-Scale Adaptive Context RAG
KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting
InfiniSST: Simultaneous Translation of Unbounded Speech with Large Language Model
RARE: Retrieval-Aware Robustness Evaluation for Retrieval-Augmented Generation Systems
Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
GPIoT: Tailoring Small Language Models for IoT Program Synthesis and Development
Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension
How Personality Traits Influence Negotiation Outcomes? A Simulation based on Large Language Models
MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Model
REARANK: Reasoning Re-ranking Agent via Reinforcement Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.