Papers with Code 아카이브
Knowledge Graph Completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 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/Jingkang50/OpenPSG
공식 코드https://github.com/Jingyu6/speculative_prefill
공식 코드https://github.com/JinheonBaek/GEN
공식 코드Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
https://github.com/Joe-Hall-Lee/Debias
공식 코드https://github.com/Joe-Hall-Lee/PSN-IRT
공식 코드Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory
https://github.com/Joe-zsc/GAP
공식 코드https://github.com/JoyDajunSpaceCraft/RAG-RLRC-LaySum
공식 코드https://github.com/Juanhui28/Are_MPNNs_helpful
공식 코드Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?
https://github.com/Jumponthemoon/WeatherDG
공식 코드https://github.com/JumpyPizza/align-sentence-simplification-with-ESL-learner
공식 코드Aligning Sentence Simplification with ESL Learner's Proficiency for Language Acquisition
https://github.com/Jundifang/PsyLite
공식 코드https://github.com/KKbeckang/LiGPT-Beta
공식 코드https://github.com/KRLabsOrg/LettuceDetect
공식 코드LettuceDetect: A Hallucination Detection Framework for RAG Applications
https://github.com/KRR-Oxford/DeepOnto
공식 코드Contextual Semantic Embeddings for Ontology Subsumption Prediction
https://github.com/KaiyueSun98/T2V-CompBench
공식 코드T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation
https://github.com/Kaylee0501/X-MLClass
공식 코드Open-world Multi-label Text Classification with Extremely Weak Supervision
https://github.com/Knowledge-aware-AI/GPTKB
공식 코드Enabling LLM Knowledge Analysis via Extensive Materialization
https://github.com/KokiKishimoto/cp_decomposition
공식 코드https://github.com/KokiKishimoto/cp_decomposition_alpha
공식 코드https://github.com/KordingLab/llm4teach-freetext-server
공식 코드A large language model-assisted education tool to provide feedback on open-ended responses
https://github.com/LAMDA-RL/CoLA
공식 코드https://github.com/LC1332/Chat-Haruhi-Suzumiya
공식 코드ChatHaruhi: Reviving Anime Character in Reality via Large Language Model
https://github.com/LHRLAB/HyperGraphRAG
공식 코드HyperGraphRAG: Retrieval-Augmented Generation with Hypergraph-Structured Knowledge Representation
https://github.com/LINs-lab/M3
공식 코드https://github.com/LL-a-VO/VLLaVO
공식 코드https://github.com/LLLQAQFFF/360REA
공식 코드https://github.com/LLer0829/Measuring_Copyright_Risk_of_LLM
공식 코드Measuring Copyright Risks of Large Language Model via Partial Information Probing
https://github.com/Leanna97/TSINR
공식 코드https://github.com/LeapLabTHU/diver-ct
공식 코드DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints
https://github.com/LemonNoel/ATransN
공식 코드An Adversarial Transfer Network for Knowledge Representation Learning
https://github.com/Li-Z-Q/DeepSolution
공식 코드https://github.com/LivNLP/Relational-Walk-for-Knowledge-Graphs
공식 코드RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding
https://github.com/LongchaoDa/SegmentAsYouWish
공식 코드Segment as You Wish -- Free-Form Language-Based Segmentation for Medical Images
https://github.com/LuciusLan/Visual-RAG
공식 코드https://github.com/Luffy03/UniBiomed
공식 코드UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.