Knowledge Graph Completion
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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/kaistAI/Janus
공식 코드Aligning to Thousands of Preferences via System Message Generalization
https://github.com/kaistAI/Prometheus
공식 코드Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
https://github.com/kaistai/generative-context-distillation
공식 코드https://github.com/kaiyin97/crsisllm
공식 코드https://github.com/kaiyuhe998/rulearn_idea
공식 코드https://github.com/kalmannet/adaptive-knet-icassp24
공식 코드Adaptive KalmanNet: Data-Driven Kalman Filter with Fast Adaptation
https://github.com/kamichanw/speculative-ensemble
공식 코드Speculative Ensemble: Fast Large Language Model Ensemble via Speculation
https://github.com/kananmahammadli/sllmbo
공식 코드Sequential Large Language Model-Based Hyper-parameter Optimization
https://github.com/kang205/MoHR
공식 코드Recommendation Through Mixtures of Heterogeneous Item Relationships
https://github.com/kangmintong/c-rag
공식 코드C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models
https://github.com/kanhatakeyama/Additional-training-Llama2
공식 코드Teaching Specific Scientific Knowledge into Large Language Models through Additional Training
https://github.com/kanyooo/biomed-dpt
공식 코드Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language Models
https://github.com/kapilsprinklr/cxmarena
공식 코드CXMArena: Unified Dataset to benchmark performance in realistic CXM Scenarios
https://github.com/karannb/interact
공식 코드Implementation and Application of an Intelligibility Protocol for Interaction with an LLM
https://github.com/karpathy/nanogpt
공식 코드OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation
https://github.com/karpurapus/bddgpt-automate-tests
공식 코드https://github.com/karthiksoman/zebra-Llama
공식 코드Zebra-Llama: A Context-Aware Large Language Model for Democratizing Rare Disease Knowledge
https://github.com/kcacozhang/lgre
공식 코드Learning Granularity Representation for Temporal Knowledge Graph Completion
https://github.com/kdr/videorag-mrr2024
공식 코드Video Enriched Retrieval Augmented Generation Using Aligned Video Captions
https://github.com/keanudicap/MSQA
공식 코드Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering
https://github.com/keke-nice/medtvt-r1
공식 코드MedTVT-R1: A Multimodal LLM Empowering Medical Reasoning and Diagnosis
https://github.com/keke-nice/period-llm
공식 코드Period-LLM: Extending the Periodic Capability of Multimodal Large Language Model
https://github.com/kel-lu/scigen
공식 코드https://github.com/kennethwdk/LocLLM
공식 코드LocLLM: Exploiting Generalizable Human Keypoint Localization via Large Language Model
https://github.com/kennyyao2001/16824-caloraify
공식 코드CaLoRAify: Calorie Estimation with Visual-Text Pairing and LoRA-Driven Visual Language Models
https://github.com/kent0n-li/chatdoctor
공식 코드https://github.com/kevinwu23/stanfordclasheval
공식 코드ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence
https://github.com/kevinyaobytedance/llm_unlearn
공식 코드https://github.com/kgrl2021/submission-one
공식 코드A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things
https://github.com/khyatikhandelwal/indian-llms-bias
공식 코드Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Models
https://github.com/kicarussays/medrep
공식 코드MedRep: Medical Concept Representation for General Electronic Health Record Foundation Models
https://github.com/kihopark/llm_categorical_hierarchical_representations
공식 코드The Geometry of Categorical and Hierarchical Concepts in Large Language Models
https://github.com/kilicogluh/lbd-covid
공식 코드Drug Repurposing for COVID-19 via Knowledge Graph Completion
https://github.com/kilimanj4r0/code-summarization-beyond-function-level
공식 코드https://github.com/kimdanny/fair-rag
공식 코드Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.