Papers with Code 아카이브
Knowledge Graphs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/causalgraph/causalgraph
공식 코드https://github.com/causalgraph/causalgraph-ontology
공식 코드https://github.com/causalkg/causallp
공식 코드CausalLP: Learning causal relations with weighted knowledge graph link prediction
https://github.com/cbhu523/chatgpt_ASD_diagnosis
공식 코드https://github.com/cciiplab/cet
공식 코드https://github.com/cciiplab/kgic
공식 코드Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning
https://github.com/ceeai/elle
공식 코드https://github.com/ceezh/llovi
공식 코드A Simple LLM Framework for Long-Range Video Question-Answering
https://github.com/chahak13/tuitus
공식 코드Enabling knowledge discovery in natural hazard engineering datasets on DesignSafe
https://github.com/chancefocus/pixiu
공식 코드PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
https://github.com/chancharikmitra/ccot
공식 코드Compositional Chain-of-Thought Prompting for Large Multimodal Models
https://github.com/changdejie/diaKG-code
공식 코드DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
https://github.com/changyi7231/ckgc
공식 코드Complex Logical Query Answering by Calibrating Knowledge Graph Completion Models
https://github.com/chantalmp/radialog
공식 코드https://github.com/charles-ydd/trojanrag
공식 코드TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models
https://github.com/chauncey-jheng/pcrl-mrg
공식 코드https://github.com/chelsielei/ez-hoi
공식 코드EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection
https://github.com/chen-yang-liu/change-agent
공식 코드Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
https://github.com/chen-zichen/xplainllm_dataset
공식 코드XplainLLM: A Knowledge-Augmented Dataset for Reliable Grounded Explanations in LLMs
https://github.com/chen700564/RGB
공식 코드Benchmarking Large Language Models in Retrieval-Augmented Generation
https://github.com/chenchens190009/csprom-kg
공식 코드https://github.com/chenchens190009/kg-s2s
공식 코드Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion
https://github.com/chendelong1999/subobjects
공식 코드https://github.com/chengjunyan1/aapm
공식 코드https://github.com/chenkaisun/socialsense
공식 코드https://github.com/chenneking/citegeist
공식 코드Citegeist: Automated Generation of Related Work Analysis on the arXiv Corpus
https://github.com/chenxran/ok-transformer
공식 코드Enhancing Natural Language Representation with Large-Scale Out-of-Domain Commonsense
https://github.com/chenyiqun/mmoa-rag
공식 코드Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
https://github.com/chenyu-jiang/megatron-lm
공식 코드DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines
https://github.com/chenzhongwu20/rulerag_icl_ft
공식 코드RuleRAG: Rule-guided retrieval-augmented generation with language models for question answering
https://github.com/cherise215/LLM-ECG-Dual-Attention
공식 코드Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
https://github.com/chiang-yuan/llamp
공식 코드https://github.com/chiangel/awesome-llm-for-recsys
공식 코드How Can Recommender Systems Benefit from Large Language Models: A Survey
https://github.com/chicosirius/think-or-not
공식 코드https://github.com/chilab1/medpix-2.0
공식 코드MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI Applications
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.