Papers with Code 아카이브

Knowledge Graphs

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 5
평가표: 4
보존된 평가 기록: 19

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.

코드

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

https://github.com/gradiustwinbee/glis

공식 코드

Global-Local Collaborative Inference with LLM for Lidar-Based Open-Vocabulary Detection

https://github.com/graph-and-geometric-learning/hypercore

공식 코드

HyperCore: The Core Framework for Building Hyperbolic Foundation Models with Comprehensive Modules

https://github.com/graph-com/subgraphrag

공식 코드

Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

https://github.com/graphcore-research/kg-topology-toolbox

공식 코드

The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models

https://github.com/graphcore-research/llm-inference-research

공식 코드

SparQ Attention: Bandwidth-Efficient LLM Inference

https://github.com/graphcore/distributed-kge-poplar

공식 코드

BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion

https://github.com/graphdeeplearning/graphtransformer

공식 코드

A Generalization of Transformer Networks to Graphs

https://github.com/graphpku/coi

공식 코드

Chain of Images for Intuitively Reasoning

https://github.com/graphpku/open-world-kg

공식 코드

Rethinking Knowledge Graph Evaluation Under the Open-World Assumption

https://github.com/graphrag-bench/graphrag-benchmark

공식 코드

When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation

https://github.com/graphresearcher/autodata

공식 코드

AutoData: A Multi-Agent System for Open Web Data Collection

https://github.com/gregorycoppola/bayes-star

공식 코드

The Quantified Boolean Bayesian Network: Theory and Experiments with a Logical Graphical Model

https://github.com/gsp2014/NaLP

공식 코드

Link Prediction on N-ary Relational Data Based on Relatedness Evaluation

https://github.com/gtfintechlab/aclready

공식 코드

ACL Ready: RAG Based Assistant for the ACL Checklist

https://github.com/guangyaodou/SSU_Unlearn

공식 코드

Avoiding Copyright Infringement via Large Language Model Unlearning

https://github.com/guanlinlee/art

공식 코드

ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users

https://github.com/guanzhou-ke/knowledge-bridger

공식 코드

Knowledge Bridger: Towards Training-free Missing Modality Completion

https://github.com/guilhermesfc/ontology-matching-absolute-orientation

공식 코드

Ontology Matching Through Absolute Orientation of Embedding Spaces

https://github.com/guinan-su/auto-merge-llm

공식 코드

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching

https://github.com/guojiapub/bique

공식 코드

BiQUE: Biquaternionic Embeddings of Knowledge Graphs

https://github.com/guopeiming/E2E_PSDG

공식 코드

An End-to-End Model for Photo-Sharing Multi-modal Dialogue Generation

https://github.com/gurdaspuriya/walk-and-relate

공식 코드

Walk-and-Relate: A Random-Walk-based Algorithm for Representation Learning on Sparse Knowledge Graphs

https://github.com/guybenyosef/echonarrator

공식 코드

EchoNarrator: Generating natural text explanations for ejection fraction predictions

https://github.com/gxnu-zhonglab/dutrack

공식 코드

Dynamic Updates for Language Adaptation in Visual-Language Tracking

https://github.com/gxym/vcapsbench

공식 코드

VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality Evaluation

https://github.com/gychant/CSKMTermDefn

공식 코드

Commonsense Knowledge Mining from Term Definitions

https://github.com/h-tayyarmadabushi/a-frame-semantics-based-approach-for-improved-factual-accuracy-in-large-language-models

공식 코드

FS-RAG: A Frame Semantics Based Approach for Improved Factual Accuracy in Large Language Models

https://github.com/h-zhao1997/cobra

공식 코드

Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference

https://github.com/h324yang/HMAN

공식 코드

Aligning Cross-Lingual Entities with Multi-Aspect Information

https://github.com/hackerchenzhuo/LaKo

공식 코드

LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection

https://github.com/hahahenha/poi-qa

공식 코드

A Dataset for Spatiotemporal-Sensitive POI Question Answering

https://github.com/hahnyuan/llm-viewer

공식 코드

LLM Inference Unveiled: Survey and Roofline Model Insights

https://github.com/haiduo/Jakiro

공식 코드

Jakiro: Boosting Speculative Decoding with Decoupled Multi-Head via MoE

https://github.com/haileyfamo/insqabench

공식 코드

InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models

https://github.com/haitaowutju/turing-machine-bench

공식 코드

Computational Reasoning of Large Language Models

https://github.com/haltiaai/paper-ptskc

공식 코드

Prompt-Time Symbolic Knowledge Capture with Large Language Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.