https://github.com/liseda-lab/seek
공식 코드Explainable Representations for Relation Prediction in Knowledge Graphs
Papers with Code 아카이브
Knowledge Graph Completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/liseda-lab/truewalks
공식 코드Biomedical Knowledge Graph Embeddings with Negative Statements
https://github.com/littleflow3r/kg-structure-as-prompt
공식 코드https://github.com/litwellchi/chatillusion
공식 코드M$^{2}$Chat: Empowering VLM for Multimodal LLM Interleaved Text-Image Generation
https://github.com/liu-hy/genotex
공식 코드GenoTEX: An LLM Agent Benchmark for Automated Gene Expression Data Analysis
https://github.com/liu-yushan/PoLo
공식 코드Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs
https://github.com/liu-yushan/tlogic
공식 코드TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs
https://github.com/liuhaogeng/anchor-former
공식 코드Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model
https://github.com/liuliuyuan6/Exp4Fuse
공식 코드https://github.com/liunian-jay/gainrag
공식 코드GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis
https://github.com/liuqidong07/LLMEmb
공식 코드LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation
https://github.com/liuqidong07/awesome-llm-enhanced-recommender-systems
공식 코드https://github.com/liuqidong07/leader-pytorch
공식 코드Large Language Model Distilling Medication Recommendation Model
https://github.com/liuran998/RelAdapter
공식 코드Context-Aware Adapter Tuning for Few-Shot Relation Learning in Knowledge Graphs
https://github.com/liushuai35/PaddleXrc
공식 코드XY-Cut++: Advanced Layout Ordering via Hierarchical Mask Mechanism on a Novel Benchmark
https://github.com/liuting20/mustdrop
공식 코드Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model
https://github.com/liuyuaa/RAM
공식 코드https://github.com/lixinze777/lc_vs_rag
공식 코드https://github.com/liyang619/cole-platform
공식 코드Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination
https://github.com/liyichen-cly/pog
공식 코드Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs
https://github.com/liyinqi/un2clip
공식 코드un$^2$CLIP: Improving CLIP's Visual Detail Capturing Ability via Inverting unCLIP
https://github.com/liyucheng09/contamination_detector
공식 코드An Open Source Data Contamination Report for Large Language Models
https://github.com/liyucs/RAGNet
공식 코드Two-Stage Single Image Reflection Removal with Reflection-Aware Guidance
https://github.com/lizhaoliu-lec/cg-vlm
공식 코드Contrastive Vision-Language Alignment Makes Efficient Instruction Learner
https://github.com/ljcleo/hi-arg
공식 코드Hi-ArG: Exploring the Integration of Hierarchical Argumentation Graphs in Language Pretraining
https://github.com/llm-as-dataset-analyst/SSDLLM
공식 코드LLM as Dataset Analyst: Subpopulation Structure Discovery with Large Language Model
https://github.com/llm-conditioned-diffusion/llm-conditioned-diffusion.github.io
공식 코드https://github.com/llm-lab-org/multimodal-rag-survey
공식 코드Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation
https://github.com/llm-platform-security/chatgpt-plugin-eval
공식 코드LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins
https://github.com/llm-random/llm-random
공식 코드Mixture of Tokens: Continuous MoE through Cross-Example Aggregation
https://github.com/llm-vlm-gsl/discuss-rag
공식 코드Talk Before You Retrieve: Agent-Led Discussions for Better RAG in Medical QA
https://github.com/llmconference/emnlp_conference_2024
공식 코드https://github.com/llmkvsys/rethink-kv-compression
공식 코드Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving
https://github.com/llqy123/dabr
공식 코드Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional Rotation
https://github.com/lm-playpen/playpen
공식 코드Playpen: An Environment for Exploring Learning Through Conversational Interaction
https://github.com/lm-sys/fastchat
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.