https://github.com/runxinxu/childtuning
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
Papers with Code 아카이브
Large Language Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ruotianluo/zsl-gcn-pth
Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs
https://github.com/sail-sg/adan
Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models
https://github.com/samleoqh/MultiModNet
https://github.com/sandai-org/magiattention
https://github.com/security-force-monitor/sfm-graph-extractor
https://github.com/semantic-systems/NLIWOD
https://github.com/sevinjt/owl2vec4oa
https://github.com/sevvalckc/Turkish-SAD
TurkishBERTweet: Fast and Reliable Large Language Model for Social Media Analysis
https://github.com/shamim-hussain/egt
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
https://github.com/shansongliu/M2UGen
Music Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning
https://github.com/shansongliu/MU-LLaMA
Music Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning
https://github.com/sheldonresearch/ProG
A Survey of Graph Meets Large Language Model: Progress and Future Directions
https://github.com/shihaozhaozsh/lavi-bridge
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
https://github.com/shijx12/kqapro_baselines
https://github.com/showlab/WorldGUI
ASSISTGUI: Task-Oriented Desktop Graphical User Interface Automation
https://github.com/shreya1313/llm-unlearning
https://github.com/sib-swiss/sparql-examples-utils
https://github.com/sid-sundrani/differentiable-kb-qa
Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection
https://github.com/sierra-research/tau-bench
$τ^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
https://github.com/skyworkai/skywork
https://github.com/sl-93/SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING
Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
https://github.com/smoothnlp/SmoothNLP
https://github.com/snap-stanford/ConE
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
https://github.com/snap-stanford/KGReasoning
https://github.com/snap-stanford/neural-subgraph-learning-gnn
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/citation2
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/collab
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/ddi
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/ppa
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/arxiv
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/mag
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/papers100M
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/products
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/proteins
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/songzeceng/KGNNLS_DEMO
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.