Papers with Code 아카이브
Knowledge Graphs
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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/jianhaochen-nju/tsdre
공식 코드Timeline-based Sentence Decomposition with In-Context Learning for Temporal Fact Extraction
https://github.com/jianlingl/llm_st_constparsing
공식 코드LLM-enhanced Self-training for Cross-domain Constituency Parsing
https://github.com/jianshuod/engorgio-prompt
공식 코드https://github.com/jianxu95/rallrec
공식 코드https://github.com/jianyu-cs/promptquine
공식 코드Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
https://github.com/jiapuwang/awesome-tkgc
공식 코드A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects
https://github.com/jiaruzouu/prb
공식 코드https://github.com/jieyilong/tree-of-thought-puzzle-solver
공식 코드https://github.com/jihaonew/mm-instruct
공식 코드MM-Instruct: Generated Visual Instructions for Large Multimodal Model Alignment
https://github.com/jiho283/FactKG
공식 코드https://github.com/jiho283/kg-gpt
공식 코드KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models
https://github.com/jimengshi/hypercube-rag
공식 코드https://github.com/jimmyma99/teleantifraud
공식 코드TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom Fraud Detection
https://github.com/jindongli-ai/next-generation-llm-based-recommender-systems-survey
공식 코드Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond
https://github.com/jinggqu/nextgen-uia
공식 코드Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis
https://github.com/jinghanzhang1998/ratt
공식 코드RATT: A Thought Structure for Coherent and Correct LLM Reasoning
https://github.com/jingkang50/openpvsg
공식 코드https://github.com/jingkang50/psg4d
공식 코드https://github.com/jinlab-imvr/medagent-pro
공식 코드MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflow
https://github.com/jiny1623/dynamicer
공식 코드DynamicER: Resolving Emerging Mentions to Dynamic Entities for RAG
https://github.com/jinyangwu/NoiserBench
공식 코드https://github.com/jinyansu1/aggd
공식 코드https://github.com/jinyansu1/eval_poisonrag
공식 코드https://github.com/jinyansu1/flare-aug
공식 코드https://github.com/jinzhuoran/rag-rewardbench
공식 코드https://github.com/jiyaowei/lp_nkgs
공식 코드https://github.com/jizhi-zhang/billp
공식 코드Large Language Models are Learnable Planners for Long-Term Recommendation
https://github.com/jizhi-zhang/fairllm
공식 코드Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
https://github.com/jizhi-zhang/rec4agentverse_case
공식 코드Prospect Personalized Recommendation on Large Language Model-based Agent Platform
https://github.com/jjcherian/conformal-safety
공식 코드Large language model validity via enhanced conformal prediction methods
https://github.com/jjzha/fs1
공식 코드Scaling Reasoning can Improve Factuality in Large Language Models
https://github.com/jjzha/sefl
공식 코드SEFL: Harnessing Large Language Model Agents to Improve Educational Feedback Systems
https://github.com/jl-wei/feature-inspiration
공식 코드Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach
https://github.com/jlab-nlp/retrieval-augmented-correction
공식 코드RAC: Efficient LLM Factuality Correction with Retrieval Augmentation
https://github.com/jlcmoore/llms-as-therapists
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.