https://github.com/yeyimilk/llm-vision-marine-animals
공식 코드Benchmarking Large Language Models for Image Classification of Marine Mammals
Papers with Code 아카이브
Benchmarking
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yeyimilk/llmgeo
공식 코드LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
https://github.com/yhydhx/chatgpt-api
공식 코드https://github.com/yhzhu99/covid-ehr-benchmarks
공식 코드https://github.com/yhzhu99/ehr-llm-benchmark
공식 코드https://github.com/yhzhu99/medagentboard
공식 코드https://github.com/yhzhu99/pyehr
공식 코드https://github.com/yhzhu99/pyehr-playground
공식 코드https://github.com/yichaolu/traffic4cast2021
공식 코드Learning to Transfer for Traffic Forecasting via Multi-task Learning
https://github.com/yichaolu/traffic4cast2022
공식 코드An Efficient Two-stage Gradient Boosting Framework for Short-term Traffic State Estimation
https://github.com/yichizhang98/sam4mis
공식 코드Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directions
https://github.com/yihong-97/oass
공식 코드https://github.com/yinghao-li/muben
공식 코드MUBen: Benchmarking the Uncertainty of Molecular Representation Models
https://github.com/yinhefeng/ANCR
공식 코드Affine Non-negative Collaborative Representation Based Pattern Classification
https://github.com/yinwenpeng/BenchmarkingZeroShot
공식 코드Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
https://github.com/yixinghuang/chatgpt-benchmark-on-radiation-oncology
공식 코드https://github.com/yixuantt/MultiHop-RAG
공식 코드MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries
https://github.com/yizhen20133868/ci-tod
공식 코드https://github.com/yizhidamiaomiao/DoppelgangerGraph
공식 코드https://github.com/ykang/gratis
공식 코드GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
https://github.com/ykang/tsgeneration
공식 코드GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
https://github.com/ykrmm/benchmarktw
공식 코드Temporal receptive field in dynamic graph learning: A comprehensive analysis
https://github.com/ylongqi/FoodDist
공식 코드Yum-me: A Personalized Nutrient-based Meal Recommender System
https://github.com/yoichii/nashpobench2api
공식 코드https://github.com/youngsoul0731/flora-bench
공식 코드https://github.com/yrf1/llm-massivemulticulturenormsknowledge-nclb
공식 코드Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking
https://github.com/ys-zong/medfair
공식 코드https://github.com/ys-zong/vl-icl
공식 코드VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning
https://github.com/ytian73/aigi-vc
공식 코드AI-generated Image Quality Assessment in Visual Communication
https://github.com/yuangpeng/dreambench_plus
공식 코드DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation
https://github.com/yueliukth/csaw-m
공식 코드CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
https://github.com/yueming-yin/gafse
공식 코드An open unified deep graph learning framework for discovering drug leads
https://github.com/yueqingliang1/unbench
공식 코드Benchmarking LLMs for Political Science: A United Nations Perspective
https://github.com/yuki-asuuna/umwp
공식 코드Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem
https://github.com/yukimasano/PASS
공식 코드PASS: An ImageNet replacement for self-supervised pretraining without humans
https://github.com/yuliang-liu/multimodalocr
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.