https://github.com/weiyanbin1999/kicgpt
공식 코드KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion
Papers with Code 아카이브
Knowledge Graphs
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- 평가표
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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/weiyifan1023/senator
공식 코드Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs
https://github.com/weiyumou/KCluster
공식 코드KCluster: An LLM-based Clustering Approach to Knowledge Component Discovery
https://github.com/weizhepei/instructrag
공식 코드InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
https://github.com/wellecks/llmstep
공식 코드https://github.com/wenboown/generative-ai-for-semiconductor-physical-design
공식 코드Enhancing Reasoning to Adapt Large Language Models for Domain-Specific Applications
https://github.com/wendy-xiao/chatgpt_editing_summ
공식 코드Personalized Abstractive Summarization by Tri-agent Generation Pipeline
https://github.com/wengsyx/lingyi
공식 코드LingYi: Medical Conversational Question Answering System based on Multi-modal Knowledge Graphs
https://github.com/wenkehuang/awesome-mllm-tuning
공식 코드Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model
https://github.com/wenqian-zhang/kcd
공식 코드KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media
https://github.com/wentao-xu/kge-cl
공식 코드KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings
https://github.com/wentaotan/mllm4text-reid
공식 코드Harnessing the Power of MLLMs for Transferable Text-to-Image Person ReID
https://github.com/weopenml/pandalm
공식 코드PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
https://github.com/westlake-autolab/biokgbench.github.io
공식 코드BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science
https://github.com/westlake-baichuan-mllm/bc-omni
공식 코드https://github.com/westlake-baichuan-mllm/ocean-omni
공식 코드https://github.com/wgcyeo/UniversalRAG
공식 코드UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities
https://github.com/wghr123/mfgdiffusion
공식 코드MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire Detection
https://github.com/wglab/mint-llm
공식 코드https://github.com/wglab/reversal_curse
공식 코드https://github.com/whcpumpkin/demand-driven-navigation
공식 코드Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation
https://github.com/which47/llmcl
공식 코드Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning
https://github.com/whu-zqh/kgan
공식 코드https://github.com/whuhsy/geo-fub
공식 코드https://github.com/wilkox/gptscreenr
공식 코드Automated title and abstract screening for scoping reviews using the GPT-4 Large Language Model
https://github.com/willemsenbram/mention-detection-vgd
공식 코드Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
https://github.com/willemsenbram/reference-resolution-via-text-generation
공식 코드Resolving References in Visually-Grounded Dialogue via Text Generation
https://github.com/william-vw/elkg
공식 코드https://github.com/williambrach/gqr
공식 코드https://github.com/williamleif/graphqembed
공식 코드https://github.com/williamliujl/Qilin-Med
공식 코드Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model
https://github.com/williamzr/recipe2plan
공식 코드https://github.com/windylee0822/trea
공식 코드TREA: Tree-Structure Reasoning Schema for Conversational Recommendation
https://github.com/wisdommllab/herln
공식 코드https://github.com/wisdomshell/freeeval
공식 코드FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models
https://github.com/wishever/mmidr
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.