https://github.com/mic-dkfz/foundation-models-for-cbmir
공식 코드Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology
Papers with Code 아카이브
Data-free Knowledge Distillation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mic-dkfz/napari-nninteractive
공식 코드https://github.com/mic-dkfz/nninteractive
공식 코드https://github.com/mic-dkfz/nnssl
공식 코드https://github.com/miccunifi/circo
공식 코드iSEARLE: Improving Textual Inversion for Zero-Shot Composed Image Retrieval
https://github.com/micdoh/XLRON
공식 코드Reinforcement Learning for Dynamic Resource Allocation in Optical Networks: Hype or Hope?
https://github.com/michaelsaxon/T2IScoreScore
공식 코드https://github.com/michaelsaxon/cococrola
공식 코드https://github.com/michalspiegel/imgtb
공식 코드IMGTB: A Framework for Machine-Generated Text Detection Benchmarking
https://github.com/microsoft/AirSim-NeurIPS2019-Drone-Racing
공식 코드https://github.com/microsoft/BIPIA
공식 코드Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models
https://github.com/microsoft/ContextualSP
공식 코드MultiSpider: Towards Benchmarking Multilingual Text-to-SQL Semantic Parsing
https://github.com/microsoft/JARVIS
공식 코드TaskBench: Benchmarking Large Language Models for Task Automation
https://github.com/microsoft/VISOR
공식 코드Benchmarking Spatial Relationships in Text-to-Image Generation
https://github.com/microsoft/deepspeed-mii
공식 코드DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference
https://github.com/microsoft/lamar-benchmark
공식 코드LaMAR: Benchmarking Localization and Mapping for Augmented Reality
https://github.com/microsoft/private-benchmarking
공식 코드TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs
https://github.com/microsoft/probts
공식 코드ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
https://github.com/microsoft/subseasonal_data
공식 코드SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
https://github.com/microsoft/subseasonal_toolkit
공식 코드SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
https://github.com/microsoft/syntheseus
공식 코드https://github.com/mihaioltean/evolve-algorithms
공식 코드https://github.com/mikelasz/benchmarking-fairness-imageupsampling
공식 코드https://github.com/mikelma/craftium
공식 코드Craftium: An Extensible Framework for Creating Reinforcement Learning Environments
https://github.com/mikewangwzhl/eeg-to-text
공식 코드https://github.com/mikivishy/fullfront
공식 코드FullFront: Benchmarking MLLMs Across the Full Front-End Engineering Workflow
https://github.com/mikudehuane/FedLaAvg
공식 코드Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability
https://github.com/mila-iqia/milabench
공식 코드https://github.com/mineanybuild/mineanybuild
공식 코드MineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agents
https://github.com/minerllabs/basalt-benchmark
공식 코드https://github.com/minghehe-nobug/svip
공식 코드Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program
https://github.com/mingsun-tse/awesome-pruning-at-initialization
공식 코드https://github.com/mingsun-tse/smile-pruning
공식 코드https://github.com/minjiyoon/cgt
공식 코드Graph Generative Model for Benchmarking Graph Neural Networks
https://github.com/minnesotanlp/cobbler
공식 코드Benchmarking Cognitive Biases in Large Language Models as Evaluators
https://github.com/minqi/wordcraft
공식 코드WordCraft: An Environment for Benchmarking Commonsense Agents
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.