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/mianzg/kgbiasdetec
공식 코드https://github.com/miccaiif/top
공식 코드https://github.com/michael-wzhu/PromptCBLUE
공식 코드PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domain
https://github.com/michellekappl/mt_gender_german
공식 코드https://github.com/michiyasunaga/dragon
공식 코드https://github.com/michiyasunaga/qagnn
공식 코드QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/microsoft/DEKCOR-CommonsenseQA
공식 코드Fusing Context Into Knowledge Graph for Commonsense Question Answering
https://github.com/microsoft/DeepSpeed
공식 코드https://github.com/microsoft/FLAML
공식 코드Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference
https://github.com/microsoft/LMOps/tree/main/LLM4Science
공식 코드https://github.com/microsoft/LMOps/tree/main/llma
공식 코드Inference with Reference: Lossless Acceleration of Large Language Models
https://github.com/microsoft/MInference
공식 코드MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
https://github.com/microsoft/Multilingual-Culture-First-Misgendering-Guardrails
공식 코드A Multilingual, Culture-First Approach to Addressing Misgendering in LLM Applications
https://github.com/microsoft/agdebugger
공식 코드Interactive Debugging and Steering of Multi-Agent AI Systems
https://github.com/microsoft/alympics
공식 코드ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI Agents
https://github.com/microsoft/competeai
공식 코드CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents
https://github.com/microsoft/conli_hallucination
공식 코드Chain of Natural Language Inference for Reducing Large Language Model Ungrounded Hallucinations
https://github.com/microsoft/defenderbench
공식 코드DefenderBench: A Toolkit for Evaluating Language Agents in Cybersecurity Environments
https://github.com/microsoft/geo-vision-labeler
공식 코드GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language Models
https://github.com/microsoft/glinthawk
공식 코드Glinthawk: A Two-Tiered Architecture for Offline LLM Inference
https://github.com/microsoft/llm-rubric
공식 코드https://github.com/microsoft/lmops
공식 코드https://github.com/microsoft/muzic
공식 코드MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models
https://github.com/microsoft/only_train_once
공식 코드HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning
https://github.com/microsoft/pike-rag
공식 코드PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
https://github.com/microsoft/rebel
공식 코드https://github.com/microsoft/recai
공식 코드RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems
https://github.com/microsoft/sammo
공식 코드https://github.com/microsoft/simxns
공식 코드https://github.com/microsoft/speecht5
공식 코드WavLLM: Towards Robust and Adaptive Speech Large Language Model
https://github.com/microsoft/synqo
공식 코드MAGIC: Generating Self-Correction Guideline for In-Context Text-to-SQL
https://github.com/microsoft/unilm
공식 코드Language Is Not All You Need: Aligning Perception with Language Models
https://github.com/microsoft/unilm/tree/master/kosmos-2
공식 코드Kosmos-2: Grounding Multimodal Large Language Models to the World
https://github.com/microsoft/wina
공식 코드WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference
https://github.com/midiyazhu/micl
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.