Inductive knowledge graph completion
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/spfrommer/ranking_manipulation_data_pipeline
공식 코드https://github.com/spotify-research/tot
공식 코드https://github.com/springcty/rag-fragility-to-linguistic-variation
공식 코드https://github.com/sprocketlab/alchemist
공식 코드The ALCHEmist: Automated Labeling 500x CHEaper Than LLM Data Annotators
https://github.com/spursgozmy/table-llava
공식 코드https://github.com/squareroot3/fusedgw-entity-alignment
공식 코드A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment
https://github.com/squareroot3/grapharena
공식 코드GraphArena: Benchmarking Large Language Models on Graph Computational Problems
https://github.com/srgrace/contextual-compression
공식 코드Contextual Compression in Retrieval-Augmented Generation for Large Language Models: A Survey
https://github.com/sshaghayeghs/llama-vs-chatgpt
공식 코드https://github.com/sshaghayeghs/llama-vs-gpt
공식 코드https://github.com/ssm123ssm/docgpt-pharm
공식 코드https://github.com/sssshivvvv/adaptbot
공식 코드https://github.com/st143575/SemPlaus-plausibleparrots
공식 코드https://github.com/stanford-futuredata/ares
공식 코드ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
https://github.com/stanford-oval/wikichat
공식 코드https://github.com/stanford-oval/wikidata-emnlp23
공식 코드https://github.com/stardust-coder/japanese-lm-med-harness
공식 코드https://github.com/starmpcc/asclepius
공식 코드Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes
https://github.com/starsuzi/adaptive-rag
공식 코드https://github.com/starsuzi/videorag
공식 코드https://github.com/start2020/awesome-timeseries-llm-fm
공식 코드https://github.com/stasl0217/KEnS
공식 코드Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer
https://github.com/stasl0217/UKGE
공식 코드https://github.com/stavc/unleashingworms-extractingdata
공식 코드https://github.com/stefanpie/hls-eval
공식 코드HLS-Eval: A Benchmark and Framework for Evaluating LLMs on High-Level Synthesis Design Tasks
https://github.com/stephen-smj/llamacare
공식 코드LlamaCare: A Large Medical Language Model for Enhancing Healthcare Knowledge Sharing
https://github.com/stephenturner/biorecap
공식 코드biorecap: an R package for summarizing bioRxiv preprints with a local LLM
https://github.com/stephlong614/causal-disco
공식 코드https://github.com/steve30572/dpao
공식 코드Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systems
https://github.com/stevengrove/gpt4tools
공식 코드GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction
https://github.com/stevenjamesmoore/learningatscale24
공식 코드Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions
https://github.com/stevenzhb/cadge
공식 코드CADGE: Context-Aware Dialogue Generation Enhanced with Graph-Structured Knowledge Aggregation
https://github.com/stochasticai/xturing
공식 코드https://github.com/stream-bench/stream-bench
공식 코드StreamBench: Towards Benchmarking Continuous Improvement of Language Agents
https://github.com/striderdu/spa
공식 코드Search to Pass Messages for Temporal Knowledge Graph Completion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.