Papers with Code 아카이브
Inductive knowledge graph completion
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/futureeeeee/dynamic-rag
공식 코드https://github.com/futureeeeee/mba
공식 코드MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexity
https://github.com/fuyu-quant/iblm
공식 코드Inductive-bias Learning: Generating Code Models with Large Language Model
https://github.com/gabriellasky/claim_optimization
공식 코드https://github.com/gair-nlp/deepresearcher
공식 코드DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments
https://github.com/gair-nlp/openresearcher
공식 코드OpenResearcher: Unleashing AI for Accelerated Scientific Research
https://github.com/gair-nlp/preference-dissection
공식 코드https://github.com/gair-nlp/prox
공식 코드Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale
https://github.com/ganjinzero/rrhf
공식 코드RRHF: Rank Responses to Align Language Models with Human Feedback without tears
https://github.com/gao-g/prelude
공식 코드Aligning LLM Agents by Learning Latent Preference from User Edits
https://github.com/gasolsun36/dynamicrag
공식 코드https://github.com/gasolsun36/surf
공식 코드SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information
https://github.com/gasolsun36/tog
공식 코드Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
https://github.com/gatech-eic/edge-llm
공식 코드https://github.com/gatenlp/h3prompt
공식 코드https://github.com/gautierdag/plancraft
공식 코드Plancraft: an evaluation dataset for planning with LLM agents
https://github.com/gavin001201/cof
공식 코드CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models
https://github.com/gblackout/TILR
공식 코드https://github.com/gchochla/vault
공식 코드VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media
https://github.com/gcyzsl/o3-llm-unlearning
공식 코드https://github.com/ge-semtk/semtk
공식 코드SemTK: An Ontology-first, Open Source Semantic Toolkit for Managing and Querying Knowledge Graphs
https://github.com/geekan/metagpt
공식 코드https://github.com/geekjuruo/beer2
공식 코드Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity Linking
https://github.com/gen-verse/scoreflow
공식 코드ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization
https://github.com/generative-social-choice/chatbot_personalization_data
공식 코드https://github.com/genetasefa/raild
공식 코드RAILD: Towards Leveraging Relation Features for Inductive Link Prediction In Knowledge Graphs
https://github.com/gengchenmai/Attention_GraphQA
공식 코드Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs
https://github.com/genggengcss/OntoZSL
공식 코드https://github.com/genggengcss/pdkgc
공식 코드Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Model
https://github.com/geobrain-ai/geogalactica
공식 코드GeoGalactica: A Scientific Large Language Model in Geoscience
https://github.com/geofila/Semantic-Counterfactuals
공식 코드Choose your Data Wisely: A Framework for Semantic Counterfactuals
https://github.com/georgiarg/autofashion
공식 코드Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models
https://github.com/geox-lab/allspark
공식 코드https://github.com/geox-lab/hook
공식 코드Homogeneous Tokenizer Matters: Homogeneous Visual Tokenizer for Remote Sensing Image Understanding
https://github.com/geox-lab/rs-gpt4v
공식 코드RS-GPT4V: A Unified Multimodal Instruction-Following Dataset for Remote Sensing Image Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.