https://github.com/OpenStellarTeam/ChineseEcomQA
공식 코드ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models
Papers with Code 아카이브
Knowledge Graph Completion
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- 보존된 평가 기록
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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/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
https://github.com/PhilippChr/CLOCQ
공식 코드https://github.com/PhilippChr/CONVEX
공식 코드https://github.com/Pie115/Learning-Matrix-Functions-In-Context
공식 코드Can a Large Language Model Learn Matrix Functions In Context?
https://github.com/Pints-AI/Finetune-Bench-RAG
공식 코드Finetune-RAG: Fine-Tuning Language Models to Resist Hallucination in Retrieval-Augmented Generation
https://github.com/PlusRoss/Hy-Transformer
공식 코드https://github.com/PrekshaNema25/Answerability-Metric
공식 코드Towards a Better Metric for Evaluating Question Generation Systems
https://github.com/Pro-GenAI/AutoPureData
공식 코드AutoPureData: Automated Filtering of Undesirable Web Data to Update LLM Knowledge
https://github.com/PrzemyslawStok/ssakg
공식 코드Associative Knowledge Graphs for Efficient Sequence Storage and Retrieval
https://github.com/PyRGL/rgl
공식 코드RGL: A Graph-Centric, Modular Framework for Efficient Retrieval-Augmented Generation on Graphs
https://github.com/Pzoom522/ProcrustEs-KGE
공식 코드Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis
https://github.com/QingkaiZeng/GenTaxo
공식 코드Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations
https://github.com/QipengGuo/CycleGT
공식 코드CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training
https://github.com/Quadflor/quadflor
공식 코드Using Titles vs. Full-text as Source for Automated Semantic Document Annotation
https://github.com/QwenLM/Qwen-7B
공식 코드https://github.com/RED-Search/Qilin
공식 코드Qilin: A Multimodal Information Retrieval Dataset with APP-level User Sessions
https://github.com/RLE-Foundation/rllte
공식 코드RLLTE: Long-Term Evolution Project of Reinforcement Learning
https://github.com/RLHFlow/RLHF-Reward-Modeling
공식 코드https://github.com/RManLuo/CP-GNN
공식 코드Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model
https://github.com/RManLuo/gfm-rag
공식 코드GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.