https://github.com/harryshomer/quad
공식 코드Learning Representations for Hyper-Relational Knowledge Graphs
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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: $(h, r, ?)$.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Learning Representations for Hyper-Relational Knowledge Graphs
Distance-Based Propagation for Efficient Knowledge Graph Reasoning
AdaptVision: Dynamic Input Scaling in MLLMs for Versatile Scene Understanding
Towards Improving Document Understanding: An Exploration on Text-Grounding via MLLMs
Streamlining the Collaborative Chain of Models into A Single Forward Pass in Generation-Based Tasks
Estimating Large Language Model Capabilities without Labeled Test Data
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Labels Generated by Large Language Model Helps Measuring People's Empathy in Vitro
An Open-World Extension to Knowledge Graph Completion Models
MEIA: Multimodal Embodied Perception and Interaction in Unknown Environments
MedMine: Examining Pre-trained Language Models on Medication Mining
Multimodal LLM-Guided Semantic Correction in Text-to-Image Diffusion
Prompting as Probing: Using Language Models for Knowledge Base Construction
TestNUC: Enhancing Test-Time Computing Approaches through Neighboring Unlabeled Data Consistency
SqueezeAttention: 2D Management of KV-Cache in LLM Inference via Layer-wise Optimal Budget
DRPruning: Efficient Large Language Model Pruning through Distributionally Robust Optimization
Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge
Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks
Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language Model
PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender System
LlamaPartialSpoof: An LLM-Driven Fake Speech Dataset Simulating Disinformation Generation
Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent Exploration
Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach
Historical Ink: 19th Century Latin American Spanish Newspaper Corpus with LLM OCR Correction
LARCH: Large Language Model-based Automatic Readme Creation with Heuristics
A LLM-Based Ranking Method for the Evaluation of Automatic Counter-Narrative Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.