https://github.com/lennijusten/biology-benchmarks
Virology Capabilities Test (VCT): A Multimodal Virology Q&A Benchmark
Papers with Code 아카이브
Knowledge Graphs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 4
- 보존된 평가 기록
- 19
A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/levon003/wiki-ores-feedback
https://github.com/lhrlab/dhge
DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity Typing
https://github.com/lightaime/camel
CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
https://github.com/linhaowei1/fine-tuning-scaling-law
Selecting Large Language Model to Fine-tune via Rectified Scaling Law
https://github.com/linzwcs/aft
Mixture-of-Agents Enhances Large Language Model Capabilities
https://github.com/liseda-lab/KGE_Predictions_GD
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies
https://github.com/litanlitudan/skyagi
https://github.com/liunian-harold-li/desco
DesCo: Learning Object Recognition with Rich Language Descriptions
https://github.com/liyan06/minicheck
RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models
https://github.com/liyichen-cly/MMEA
https://github.com/liyichen-cly/MSNEA
https://github.com/lizli502/sse-pt
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
https://github.com/llavar/llavar-2
https://github.com/lllyasviel/omost
https://github.com/llm-lab-org/CLASP
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
https://github.com/llm4eval/LLMJudge
Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval
https://github.com/lluckyyh/xtrust
Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models
https://github.com/lm-sys/routellm
https://github.com/lmcache/lmcache
CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving
https://github.com/lntzm/cvpr24track-longvideo
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding
https://github.com/logic-reasoning/Paper-Reading
https://github.com/lucas-ventura/chapter-llama
Chapter-Llama: Efficient Chaptering in Hour-Long Videos with LLMs
https://github.com/lucidrains/muse-pytorch
Muse: Text-To-Image Generation via Masked Generative Transformers
https://github.com/lyqcom/mindspore_nlp_tutorial
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/m42-health/med42
Clinical Camel: An Open Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding
https://github.com/magicyang1573/llm-hardware-test-generation
https://github.com/mainuliitkgp/KG-ALSC
https://github.com/mali-git/CSQA_Implementation
https://github.com/mandiehyewon/TPAMTL
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
https://github.com/marker-inc-korea/autorag
AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline
https://github.com/masakicktashiro/rgcn_pytorch_implementation
https://github.com/matlabmtl/Reco-KGNN-LS
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
https://github.com/maziao/M2RAG
https://github.com/mediabrain-sjtu/medicalgpt-zh
https://github.com/mem0ai/mem0
Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.