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Knowledge Graph Completion

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하위 태스크: 4
평가표: 7
보존된 평가 기록: 17

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: $(h, r, ?)$.

Source: One-Shot Relational Learning for Knowledge Graphs

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/METR/ai-rd-tasks

공식 코드

RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts

https://github.com/MIRALab-USTC/KGE-DURA

공식 코드

Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion

https://github.com/MIRALab-USTC/KGE-HAKE

공식 코드

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

https://github.com/MJinXiang/Reasoning-Table

공식 코드

Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning

https://github.com/MLE-Dojo/MLE-Dojo

공식 코드

MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering

https://github.com/MYC000801/SE-POPO

공식 코드

Avoiding $\mathbf{exp(R_{max})}$ scaling in RLHF through Preference-based Exploration

https://github.com/MYVAE/Instruction-detection

공식 코드

Defending against Indirect Prompt Injection by Instruction Detection

https://github.com/MaastrichtU-IDS/LMKBC-2023

공식 코드

Expanding the Vocabulary of BERT for Knowledge Base Construction

https://github.com/MadryLab/platinum-benchmarks

공식 코드

Do Large Language Model Benchmarks Test Reliability?

https://github.com/MarcoMeter/neroRL

공식 코드

Playing Pokémon Red via Deep Reinforcement Learning

https://github.com/MartinBoeckling/KGRag

공식 코드

Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks

https://github.com/MarwahAlaofi/SIGIR-23-SRP-UQV100-GPT-Query-Variants

공식 코드

Can Generative LLMs Create Query Variants for Test Collections? An Exploratory Study

https://github.com/Maxpa1n/gcplm-kgc

공식 코드

Multilingual Knowledge Graph Completion from Pretrained Language Models with Knowledge Constraints

https://github.com/MedHK23/MedViLaM

공식 코드

MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

https://github.com/MikeGu721/DetectBench

공식 코드

DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence?

https://github.com/MiliLab/GeoLLaVA-8K

공식 코드

GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution

https://github.com/Miracle1207/Mean-Field-LLM

공식 코드

MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework

https://github.com/MiuLab/RAG-Self-Preference

공식 코드

LLMs are Biased Evaluators But Not Biased for Retrieval Augmented Generation

https://github.com/MooreThreads/TurboRAG

공식 코드

TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text

https://github.com/MrRezaeiUofT/AT-RAG

공식 코드

AT-RAG: An Adaptive RAG Model Enhancing Query Efficiency with Topic Filtering and Iterative Reasoning

https://github.com/MrZihan/NavRAG

공식 코드

NavRAG: Generating User Demand Instructions for Embodied Navigation through Retrieval-Augmented LLM

https://github.com/MultimodalGeo/GeoText-1652

공식 코드

Towards Natural Language-Guided Drones: GeoText-1652 Benchmark with Spatial Relation Matching

https://github.com/MurrayTom/SG-Bench

공식 코드

SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types

https://github.com/NExT-GPT/NExT-GPT

공식 코드

NExT-GPT: Any-to-Any Multimodal LLM

https://github.com/NIVA-Knowledge-Graph/TERA

공식 코드

Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

https://github.com/NJU-LHRS/LHRS-Bot

공식 코드

LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation

https://github.com/NLPJCL/RAG-Retrieval

공식 코드

Jasper and Stella: distillation of SOTA embedding models

https://github.com/NVIDIA/Megatron-LM

공식 코드

End-to-End Training of Neural Retrievers for Open-Domain Question Answering

https://github.com/NVlabs/FoundationStereo

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FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects

https://github.com/NY1024/BAP-Jailbreak-Vision-Language-Models-via-Bi-Modal-Adversarial-Prompt

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Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt

https://github.com/NanxuGong/ELLM-FT

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Evolutionary Large Language Model for Automated Feature Transformation

https://github.com/Nickolas-option/QA_on_Tabular_Data_SemEval2025_Task8

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Bridging the Gap Between Open-Source and Proprietary LLMs in Table QA

https://github.com/Nouf-Alabbasi/oKUmura_AI_Telecom_challenge

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Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards

https://github.com/OPPOMKLab/u-LLaVA

공식 코드

u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model

https://github.com/OPTML-Group/Unlearn-Simple

공식 코드

Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning

https://github.com/OSU-NLP-Group/KG-R3

공식 코드

A Retrieve-and-Read Framework for Knowledge Graph Link Prediction

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