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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/NVIDIA/Megatron-LM
공식 코드End-to-End Training of Neural Retrievers for Open-Domain Question Answering
https://github.com/NVlabs/FoundationStereo
공식 코드FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects
https://github.com/NY1024/BAP-Jailbreak-Vision-Language-Models-via-Bi-Modal-Adversarial-Prompt
공식 코드Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt
https://github.com/NacyNiko/HGE
공식 코드HGE: Embedding Temporal Knowledge Graphs in a Product Space of Heterogeneous Geometric Subspaces
https://github.com/NanxuGong/ELLM-FT
공식 코드Evolutionary Large Language Model for Automated Feature Transformation
https://github.com/Nickolas-option/QA_on_Tabular_Data_SemEval2025_Task8
공식 코드Bridging the Gap Between Open-Source and Proprietary LLMs in Table QA
https://github.com/NicolasTe/osm2kg
공식 코드https://github.com/NikeHop/CSRL
공식 코드https://github.com/Nouf-Alabbasi/oKUmura_AI_Telecom_challenge
공식 코드Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards
https://github.com/OPPOMKLab/u-LLaVA
공식 코드u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model
https://github.com/OPTML-Group/Unlearn-Simple
공식 코드Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
https://github.com/OceannTwT/Tool-Planner
공식 코드Tool-Planner: Task Planning with Clusters across Multiple Tools
https://github.com/OmarErak/LLM-CL
공식 코드Large Language Model-Driven Curriculum Design for Mobile Networks
https://github.com/OpenBMB/AgentCPM-GUI
공식 코드AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning
https://github.com/OpenBioLink/SAFRAN
공식 코드Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs
https://github.com/OpenDFM/MobA
공식 코드MobA: Multifaceted Memory-Enhanced Adaptive Planning for Efficient Mobile Task Automation
https://github.com/OpenISS/kg-recommendation-framework
공식 코드Application of Knowledge Graphs to Provide Side Information for Improved Recommendation Accuracy
https://github.com/OpenSparseLLMs/CLIP-MoE
공식 코드CLIP-MoE: Towards Building Mixture of Experts for CLIP with Diversified Multiplet Upcycling
https://github.com/OpenStellarTeam/ChineseEcomQA
공식 코드ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models
https://github.com/PJLab-ADG/driveLikeAHuman
공식 코드Drive Like a Human: Rethinking Autonomous Driving with Large Language Models
https://github.com/PKU-YuanGroup/LLMBind
공식 코드https://github.com/PKU-YuanGroup/Video-LLaVA
공식 코드Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/PKUDigitalHealth/KidneyTalk-open
공식 코드https://github.com/PLUM-Lab/AR-RAG
공식 코드AR-RAG: Autoregressive Retrieval Augmentation for Image Generation
https://github.com/PaddlePaddle/PGL
공식 코드Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning
https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/drug_target_interaction/sman
공식 코드Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction
https://github.com/PaddlePaddle/PaddleMIX
공식 코드PP-DocBee: Improving Multimodal Document Understanding Through a Bag of Tricks
https://github.com/PaddlePaddle/Research/tree/master/KG/ACL2021_GRAN
공식 코드Link Prediction on N-ary Relational Facts: A Graph-based Approach
https://github.com/PaddlePaddle/Research/tree/master/NLP/EMNLP2019-AKGCM
공식 코드Knowledge Aware Conversation Generation with Explainable Reasoning over Augmented Graphs
https://github.com/Panda0406/Zero-shot-knowledge-graph-relational-learning
공식 코드Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs
https://github.com/Parry-Parry/terrier_trec_2023
공식 코드https://github.com/PascalSun/TimelineKGQA
공식 코드TimelineKGQA: A Comprehensive Question-Answer Pair Generator for Temporal Knowledge Graphs
https://github.com/Pascalson/DyKGChat
공식 코드DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs
https://github.com/PasiniSamuele/Robust-Attack-Detectors-LLM
공식 코드Evaluating and Improving the Robustness of Security Attack Detectors Generated by LLMs
https://github.com/Peter7Yao/OPTransE
공식 코드Representation Learning with Ordered Relation Paths for Knowledge Graph Completion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.