https://github.com/asahi417/relbert
공식 코드Distilling Relation Embeddings from Pre-trained Language Models
Papers with Code 아카이브
Knowledge Graph Completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 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: $(h, r, ?)$.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/asappresearch/halugen
공식 코드https://github.com/asappresearch/josh-llm-simulation-training
공식 코드https://github.com/ascherp/semantic-web-primer
공식 코드https://github.com/asgaardlab/LLMxBugs
공식 코드Large Language Models are Pretty Good Zero-Shot Video Game Bug Detectors
https://github.com/ash-ai-safety-hub/g3-nandi
공식 코드Comparing Optimization Targets for Contrast-Consistent Search
https://github.com/ashfarhangi/Protoformer
공식 코드https://github.com/asinghcsu/agenticrag-survey
공식 코드Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG
https://github.com/asoulet/superficiality
공식 코드The Structure and Dynamics of Knowledge Graphs, with Superficiality
https://github.com/assassinws/llm-tamp
공식 코드LLM3:Large Language Model-based Task and Motion Planning with Motion Failure Reasoning
https://github.com/astral-group/bdc_mitigation_assessment
공식 코드https://github.com/astrazeneca/awesome-drug-discovery-knowledge-graphs
공식 코드A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective
https://github.com/astrazeneca/biomedical-kg-topological-imbalance
공식 코드Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs
https://github.com/astrazeneca/kgem-in-drug-discovery
공식 코드Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery
https://github.com/astrazeneca/onto_merger
공식 코드OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes
https://github.com/asu-kim/personal-llm-kg
공식 코드Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
https://github.com/atenanaz/poison-rag
공식 코드https://github.com/augustinLib/SPIKE
공식 코드Imagine All The Relevance: Scenario-Profiled Indexing with Knowledge Expansion for Dense Retrieval
https://github.com/autextification/AuTexTification-Overview
공식 코드https://github.com/auto-icd-coding/ruccod
공식 코드https://github.com/avdpro/ai2apps
공식 코드AI2Apps: A Visual IDE for Building LLM-based AI Agent Applications
https://github.com/avinashsai/ViRED
공식 코드https://github.com/awslabs/graphrag-toolkit
공식 코드https://github.com/awslabs/hlat
공식 코드HLAT: High-quality Large Language Model Pre-trained on AWS Trainium
https://github.com/awslabs/optimizing-multitask-training-through-dynamic-pipelines
공식 코드DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines
https://github.com/awslabs/rag-qa-arena
공식 코드RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering
https://github.com/ayushraina10/sgts
공식 코드https://github.com/azminewasi/banglaautokg
공식 코드BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering
https://github.com/azminewasi/hrgraph
공식 코드https://github.com/azreasoners/llm-asp
공식 코드Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text
https://github.com/baai-dcai/m3d
공식 코드M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models
https://github.com/babahui/progressive-text-to-image
공식 코드Progressive Text-to-Image Diffusion with Soft Latent Direction
https://github.com/baharefatemi/ReAlE
공식 코드https://github.com/bahuia/hgnet
공식 코드https://github.com/bai-lab/emotionalrag
공식 코드Emotional RAG: Enhancing Role-Playing Agents through Emotional Retrieval
https://github.com/bai-lab/kg-retriever
공식 코드KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.