Papers with Code 아카이브
Inductive knowledge graph completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 3
- 보존된 평가 기록
- 6
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/duyguislakoglu/temt
공식 코드https://github.com/dvlab-research/LLMGA
공식 코드LLMGA: Multimodal Large Language Model based Generation Assistant
https://github.com/dvlab-research/diaggsm8k
공식 코드MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation
https://github.com/dvlab-research/lisa
공식 코드https://github.com/dvlab-research/mr-gsm8k
공식 코드MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation
https://github.com/dwslab/jRDF2Vec
공식 코드RDF2Vec Light -- A Lightweight Approach for Knowledge Graph Embeddings
https://github.com/dwzhu-pku/longembed
공식 코드LongEmbed: Extending Embedding Models for Long Context Retrieval
https://github.com/dxlong2000/multi-expert-prompting
공식 코드Multi-expert Prompting Improves Reliability, Safety, and Usefulness of Large Language Models
https://github.com/dyabel/anytool
공식 코드AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
https://github.com/dyang67/GammaE
공식 코드GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphs
https://github.com/eachsheep/ragsynth
공식 코드RAGSynth: Synthetic Data for Robust and Faithful RAG Component Optimization
https://github.com/earth-insights/segearth-r1
공식 코드SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model
https://github.com/eason-li-ais/drafterbench
공식 코드DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil Engineering
https://github.com/easonxiao-888/mindomni
공식 코드MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO
https://github.com/eastha0526/beyond-ontology-in-dst
공식 코드Beyond Ontology in Dialogue State Tracking for Goal-Oriented Chatbot
https://github.com/ecnu-text-computing/imsm
공식 코드https://github.com/ecofri/cxr_llava
공식 코드CXR-LLAVA: a multimodal large language model for interpreting chest X-ray images
https://github.com/ecrows/in-bloom
공식 코드In BLOOM: Creativity and Affinity in Artificial Lyrics and Art
https://github.com/edavalosanaya/LLMsAsEducationalAnalysts
공식 코드https://github.com/eddiegaoo/apt-serve
공식 코드Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving
https://github.com/edgaere/datetime
공식 코드DATETIME: A new benchmark to measure LLM translation and reasoning capabilities
https://github.com/edinburghnlp/mmlongbench
공식 코드MMLongBench: Benchmarking Long-Context Vision-Language Models Effectively and Thoroughly
https://github.com/edinburghnlp/spice
공식 코드Semantic Parsing for Conversational Question Answering over Knowledge Graphs
https://github.com/edisonni-hku/diras
공식 코드DIRAS: Efficient LLM Annotation of Document Relevance in Retrieval Augmented Generation
https://github.com/edisutoyo/satd-augmentation
공식 코드Deep Learning and Data Augmentation for Detecting Self-Admitted Technical Debt
https://github.com/edward-sun/pit
공식 코드Instruction-tuned Language Models are Better Knowledge Learners
https://github.com/egilron/afrisenti-semeval-2023
공식 코드https://github.com/ehsanlatif/g-sciedbert
공식 코드G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
https://github.com/ejaasaari/lorann
공식 코드LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
https://github.com/ejaasaari/lorann-experiments
공식 코드LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
https://github.com/ekrxjwh2009/R2-KG
공식 코드R2-KG: General-Purpose Dual-Agent Framework for Reliable Reasoning on Knowledge Graphs
https://github.com/elakhatibi/cdf-rag
공식 코드CDF-RAG: Causal Dynamic Feedback for Adaptive Retrieval-Augmented Generation
https://github.com/elated-sawyer/WALL-E
공식 코드WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
https://github.com/eleurent/highway-env
공식 코드https://github.com/eleutherai/gpt-neox
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.