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Large Language Model
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/i40-Tools/I40KG-Embeddings
공식 코드Unveiling Relations in the Industry 4.0 Standards Landscape based on Knowledge Graph Embeddings
https://github.com/iDEA-iSAIL-Lab-UIUC/APEX
공식 코드APEX$^2$: Adaptive and Extreme Summarization for Personalized Knowledge Graphs
https://github.com/iaar-shanghai/crud_rag
공식 코드https://github.com/iaar-shanghai/datg
공식 코드Controlled Text Generation for Large Language Model with Dynamic Attribute Graphs
https://github.com/iaar-shanghai/pgrag
공식 코드Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learning
https://github.com/iaar-shanghai/saferag
공식 코드SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model
https://github.com/iai-group/ginger-response-generation
공식 코드GINGER: Grounded Information Nugget-Based Generation of Responses
https://github.com/iai-group/pkg-api
공식 코드https://github.com/iamgmujtaba/scholar_search
공식 코드ChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey
https://github.com/iamryanshengwang/prometheus-chatbot
공식 코드https://github.com/ianhuang0630/aladdin
공식 코드Aladdin: Zero-Shot Hallucination of Stylized 3D Assets from Abstract Scene Descriptions
https://github.com/iankur/vqllm
공식 코드Residual vector quantization for KV cache compression in large language model
https://github.com/ibalazevic/HypER
공식 코드https://github.com/ibalazevic/TuckER
공식 코드https://github.com/ibalazevic/multirelational-poincare
공식 코드https://github.com/ibm-ecosystem-engineering/blended-rag
공식 코드https://github.com/ibm-granite/granite-guardian
공식 코드https://github.com/ibm/clai
공식 코드Project CLAI: Instrumenting the Command Line as a New Environment for AI Agents
https://github.com/ibm/data-prep-kit
공식 코드Data-Prep-Kit: getting your data ready for LLM application development
https://github.com/ibm/digital-twin-benchmark-model
공식 코드https://github.com/ibm/hspo-ontology
공식 코드Representation Learning for Person or Entity-centric Knowledge Graphs: An Application in Healthcare
https://github.com/ibm/kgi-slot-filling
공식 코드Robust Retrieval Augmented Generation for Zero-shot Slot Filling
https://github.com/ibm/lprules
공식 코드https://github.com/ibm/mt-rag-benchmark
공식 코드MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems
https://github.com/ibm/otter-knowledge
공식 코드https://github.com/ibm/sax4bpm
공식 코드How well can a large language model explain business processes as perceived by users?
https://github.com/ibndias/cipher
공식 코드CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher
https://github.com/ibpa/kglm
공식 코드KGLM: Integrating Knowledge Graph Structure in Language Models for Link Prediction
https://github.com/ibrahimethemhamamci/ct-clip
공식 코드Developing Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography
https://github.com/ibrahimethemhamamci/generatect
공식 코드GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes
https://github.com/icedpanda/COMPASS-official
공식 코드https://github.com/icedpanda/KERL
공식 코드https://github.com/icip-cas/selfretrieval
공식 코드Self-Retrieval: End-to-End Information Retrieval with One Large Language Model
https://github.com/icpc2024-so/icpc-2024
공식 코드https://github.com/ict-bigdatalab/rc-rag
공식 코드Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting Framework
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.