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/cloud-qu/lare

공식 코드

Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning

https://github.com/cmavro/gnn-rag

공식 코드

GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning

https://github.com/cmavro/rearev_kgqa

공식 코드

ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs

https://github.com/cmavro/tempoqr

공식 코드

TempoQR: Temporal Question Reasoning over Knowledge Graphs

https://github.com/cmbagents/cmbagent

공식 코드

Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery

https://github.com/cmubig/ccub

공식 코드

Towards Equitable Representation in Text-to-Image Synthesis Models with the Cross-Cultural Understanding Benchmark (CCUB) Dataset

https://github.com/cnfaker/llava-sp

공식 코드

LLaVA-SP: Enhancing Visual Representation with Visual Spatial Tokens for MLLMs

https://github.com/cobypenso/local-differential-private-conformal-prediction

공식 코드

Privacy-Preserving Conformal Prediction Under Local Differential Privacy

https://github.com/cocacola-lab/collabkg

공식 코드

CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction

https://github.com/cocacola-lab/mineland

공식 코드

MineLand: Simulating Large-Scale Multi-Agent Interactions with Limited Multimodal Senses and Physical Needs

https://github.com/code-rag-bench/code-rag-bench

공식 코드

CodeRAG-Bench: Can Retrieval Augment Code Generation?

https://github.com/code4paper-2024/code4paper

공식 코드

Harnessing the Power of Large Language Model for Uncertainty Aware Graph Processing

https://github.com/codemonsterphd/pneumollm

공식 코드

PneumoLLM: Harnessing the Power of Large Language Model for Pneumoconiosis Diagnosis

https://github.com/coderj-one/giraffe-bench

공식 코드

Benchmarking Sequential Visual Input Reasoning and Prediction in Multimodal Large Language Models

https://github.com/codesfornlp/otiea

공식 코드

OTIEA:Ontology-enhanced Triple Intrinsic-Correlation for Cross-lingual Entity Alignment

https://github.com/codesfornlp/ttea

공식 코드

Type-enhanced Ensemble Triple Representation via Triple-aware Attention for Cross-lingual Entity Alignment

https://github.com/cods-gcs/chatty-gen

공식 코드

Dialogue Benchmark Generation from Knowledge Graphs with Cost-Effective Retrieval-Augmented LLMs

https://github.com/cods-gcs/kglids

공식 코드

KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science

https://github.com/cods-gcs/kgqan

공식 코드

A Universal Question-Answering Platform for Knowledge Graphs

https://github.com/cods-gcs/kgtosa

공식 코드

Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling

https://github.com/cofe-ai/msg

공식 코드

Masked Structural Growth for 2x Faster Language Model Pre-training

https://github.com/cofe-ai/oifc

공식 코드

Open-domain Implicit Format Control for Large Language Model Generation

https://github.com/cognitiveailab/darmok

공식 코드

Picard understanding Darmok: A Dataset and Model for Metaphor-Rich Translation in a Constructed Language

https://github.com/cohere-ai/magikarp

공식 코드

Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models

https://github.com/coldchair/cpret

공식 코드

CPRet: A Dataset, Benchmark, and Model for Retrieval in Competitive Programming

https://github.com/coldmist-lu/agentexit

공식 코드

Runaway is Ashamed, But Helpful: On the Early-Exit Behavior of Large Language Model-based Agents in Embodied Environments

https://github.com/colfeng/calm

공식 코드

Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models

https://github.com/collinzrj/adversarial_decoding

공식 코드

Adversarial Decoding: Generating Readable Documents for Adversarial Objectives

https://github.com/colonylabs/ScribeAgent

공식 코드

ScribeAgent: Towards Specialized Web Agents Using Production-Scale Workflow Data

https://github.com/comind-ml/comind

공식 코드

Towards Community-Driven Agents for Machine Learning Engineering

https://github.com/comp-well-org/esi

공식 코드

ECG Semantic Integrator (ESI): A Foundation ECG Model Pretrained with LLM-Enhanced Cardiological Text

https://github.com/comp1511unsw/dcc

공식 코드

Dcc --help: Generating Context-Aware Compiler Error Explanations with Large Language Models

https://github.com/concyclics/logquantkv

공식 코드

LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy Preservation

https://github.com/congressRA/sample-agent

공식 코드

Agent-Enhanced Large Language Models for Researching Political Institutions

https://github.com/congvvc/HyperSeg

공식 코드

HyperSeg: Towards Universal Visual Segmentation with Large Language Model

https://github.com/contextualai/gritlm

공식 코드

Generative Representational Instruction Tuning

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