https://github.com/hackerchenzhuo/LaKo
공식 코드LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection
Papers with Code 아카이브
Knowledge Graphs
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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/haltiaai/paper-ptskc
공식 코드Prompt-Time Symbolic Knowledge Capture with Large Language Models
https://github.com/haochenliu2000/kelp
공식 코드Knowledge Graph-Enhanced Large Language Models via Path Selection
https://github.com/happen2me/subgraph-retrieval-toolkit
공식 코드https://github.com/harrialx/security-risk-kg-reasoning
공식 코드https://github.com/harryshomer/kg-mixup
공식 코드Toward Degree Bias in Embedding-Based Knowledge Graph Completion
https://github.com/harryshomer/quad
공식 코드Learning Representations for Hyper-Relational Knowledge Graphs
https://github.com/harryshomer/tagnet
공식 코드Distance-Based Propagation for Efficient Knowledge Graph Reasoning
https://github.com/healthylaife/ConTextual
공식 코드https://github.com/healthylaife/autofair
공식 코드Enabling Scalable Evaluation of Bias Patterns in Medical LLMs
https://github.com/heidelberg-nlp/cckg
공식 코드https://github.com/heidelberg-nlp/graphlanguagemodels
공식 코드https://github.com/hellisotherpeople/debatekg
공식 코드DebateKG: Automatic Policy Debate Case Creation with Semantic Knowledge Graphs
https://github.com/heraclex12/NLP2SPARQL
공식 코드https://github.com/hermannkroll/rankingnarrativequerygraphs
공식 코드Ranking Narrative Query Graphs for Biomedical Document Retrieval (Technical Report)
https://github.com/hermannkroll/supervisedtextprocessing
공식 코드https://github.com/hestiasky/imf-pytorch
공식 코드IMF: Interactive Multimodal Fusion Model for Link Prediction
https://github.com/hhenryd/tap
공식 코드Tree of Attributes Prompt Learning for Vision-Language Models
https://github.com/hhy-huang/graphjudge
공식 코드Can LLMs be Good Graph Judge for Knowledge Graph Construction?
https://github.com/hit-ices/tnnls-mtgn
공식 코드Who Should I Engage with At What Time? A Missing Event Aware Temporal Graph Neural Network
https://github.com/hkuds/diffkg
공식 코드https://github.com/hkuds/videorag
공식 코드VideoRAG: Retrieval-Augmented Generation with Extreme Long-Context Videos
https://github.com/hkust-knowcomp/abductivekgr
공식 코드Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generation
https://github.com/hkust-knowcomp/atomic-conceptualization
공식 코드Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization
https://github.com/hkust-knowcomp/autoschemakg
공식 코드https://github.com/hkust-knowcomp/ceqa
공식 코드Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
https://github.com/hkust-knowcomp/co2lm
공식 코드CoCoLM: COmplex COmmonsense Enhanced Language Model with Discourse Relations
https://github.com/hkust-knowcomp/efo-1-qa-benchmark
공식 코드Benchmarking the Combinatorial Generalizability of Complex Query Answering on Knowledge Graphs
https://github.com/hkust-knowcomp/efok-cqa
공식 코드$\text{EFO}_{k}$-CQA: Towards Knowledge Graph Complex Query Answering beyond Set Operation
https://github.com/hkust-knowcomp/eventground
공식 코드EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge Graphs
https://github.com/hkust-knowcomp/fit
공식 코드Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors
https://github.com/hkust-knowcomp/gold
공식 코드Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection
https://github.com/hkust-knowcomp/lmpnn
공식 코드Logical Message Passing Networks with One-hop Inference on Atomic Formulas
https://github.com/hkust-knowcomp/mico
공식 코드MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation
https://github.com/hkust-knowcomp/nrn
공식 코드Knowledge Graph Reasoning over Entities and Numerical Values
https://github.com/hkust-knowcomp/pipenet
공식 코드PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.