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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/causalgraph/causalgraph
공식 코드https://github.com/causalgraph/causalgraph-ontology
공식 코드https://github.com/causalkg/causallp
공식 코드CausalLP: Learning causal relations with weighted knowledge graph link prediction
https://github.com/cbhu523/chatgpt_ASD_diagnosis
공식 코드https://github.com/cciiplab/cet
공식 코드https://github.com/cciiplab/kgic
공식 코드Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning
https://github.com/ceeai/elle
공식 코드https://github.com/ceezh/llovi
공식 코드A Simple LLM Framework for Long-Range Video Question-Answering
https://github.com/chahak13/tuitus
공식 코드Enabling knowledge discovery in natural hazard engineering datasets on DesignSafe
https://github.com/chancefocus/pixiu
공식 코드PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
https://github.com/chancharikmitra/ccot
공식 코드Compositional Chain-of-Thought Prompting for Large Multimodal Models
https://github.com/changdejie/diaKG-code
공식 코드DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
https://github.com/changyi7231/ckgc
공식 코드Complex Logical Query Answering by Calibrating Knowledge Graph Completion Models
https://github.com/chantalmp/radialog
공식 코드https://github.com/charles-ydd/trojanrag
공식 코드TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models
https://github.com/chauncey-jheng/pcrl-mrg
공식 코드https://github.com/chelsielei/ez-hoi
공식 코드EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection
https://github.com/chen-yang-liu/change-agent
공식 코드Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
https://github.com/chen-zichen/xplainllm_dataset
공식 코드XplainLLM: A Knowledge-Augmented Dataset for Reliable Grounded Explanations in LLMs
https://github.com/chen700564/RGB
공식 코드Benchmarking Large Language Models in Retrieval-Augmented Generation
https://github.com/chenchens190009/csprom-kg
공식 코드https://github.com/chenchens190009/kg-s2s
공식 코드Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion
https://github.com/chendelong1999/subobjects
공식 코드https://github.com/chengjunyan1/aapm
공식 코드https://github.com/chenkaisun/socialsense
공식 코드https://github.com/chenneking/citegeist
공식 코드Citegeist: Automated Generation of Related Work Analysis on the arXiv Corpus
https://github.com/chenxran/ok-transformer
공식 코드Enhancing Natural Language Representation with Large-Scale Out-of-Domain Commonsense
https://github.com/chenyiqun/mmoa-rag
공식 코드Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
https://github.com/chenyu-jiang/megatron-lm
공식 코드DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines
https://github.com/chenzhongwu20/rulerag_icl_ft
공식 코드RuleRAG: Rule-guided retrieval-augmented generation with language models for question answering
https://github.com/cherise215/LLM-ECG-Dual-Attention
공식 코드Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
https://github.com/chiang-yuan/llamp
공식 코드https://github.com/chiangel/awesome-llm-for-recsys
공식 코드How Can Recommender Systems Benefit from Large Language Models: A Survey
https://github.com/chicosirius/think-or-not
공식 코드https://github.com/chilab1/medpix-2.0
공식 코드MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI Applications
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.