https://github.com/sphere-ai-lab/formalmath-bench
공식 코드FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models
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/spiral-med/diagnosisarena
공식 코드DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models
https://github.com/spotify-research/tot
공식 코드https://github.com/spring-epfl/iccwd
공식 코드A Manually Annotated Image-Caption Dataset for Detecting Children in the Wild
https://github.com/sprinter1999/fnbench
공식 코드FNBench: Benchmarking Robust Federated Learning against Noisy Labels
https://github.com/squareroot3/gadbench
공식 코드GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
https://github.com/squareroot3/grapharena
공식 코드GraphArena: Benchmarking Large Language Models on Graph Computational Problems
https://github.com/sri-karthik-avala/capsule-challenge-2024
공식 코드Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy
https://github.com/srikarym/CCTV-Gun
공식 코드https://github.com/ssarfraz/QuoVadisTAD
공식 코드Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
https://github.com/ssskj/herolt
공식 코드Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
https://github.com/ssydasheng/predictive-correlation-benchmark
공식 코드https://github.com/stacs-cp/autoig
공식 코드https://github.com/stanford-crfm/helm
공식 코드Image2Struct: Benchmarking Structure Extraction for Vision-Language Models
https://github.com/stanfordmlgroup/cheXphoto
공식 코드https://github.com/stanfordmlgroup/medagentbench
공식 코드MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents
https://github.com/star-center/ros_mp4
공식 코드High-Quality, ROS Compatible Video Encoding and Decoding for High-Definition Datasets
https://github.com/stavrosorf/ev2gym
공식 코드EV2Gym: A Flexible V2G Simulator for EV Smart Charging Research and Benchmarking
https://github.com/stegmaierj/CellSynthesis
공식 코드3D fluorescence microscopy data synthesis for segmentation and benchmarking
https://github.com/stepjam/ARM
공식 코드https://github.com/stepmat/ContinuousInformationGain
공식 코드A Continuous Information Gain Measure to Find the Most Discriminatory Problems for AI Benchmarking
https://github.com/stern5497/doc2docbeirir
공식 코드One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support
https://github.com/stogiannidis/srbench
공식 코드Mind the Gap: Benchmarking Spatial Reasoning in Vision-Language Models
https://github.com/stonybrooknlp/appworld
공식 코드AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
https://github.com/stream-bench/stream-bench
공식 코드StreamBench: Towards Benchmarking Continuous Improvement of Language Agents
https://github.com/sunblaze-ucb/llm-api-audit
공식 코드Are You Getting What You Pay For? Auditing Model Substitution in LLM APIs
https://github.com/sunblaze-ucb/verina
공식 코드https://github.com/sunnweiwei/co-bench
공식 코드CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization
https://github.com/sunnyhaze/iml-vit
공식 코드IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformer
https://github.com/suntongtongtong/benchmark-robustness-text-image-compose-retrieval
공식 코드https://github.com/superallen13/GCondenser
공식 코드https://github.com/superjamessyx/robustness_benchmark
공식 코드Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology
https://github.com/supertext/evaluation_deepl_supertext
공식 코드A comparison of translation performance between DeepL and Supertext
https://github.com/suscom-lab/wattsonai
공식 코드WattsOnAI: Measuring, Analyzing, and Visualizing Energy and Carbon Footprint of AI Workloads
https://github.com/swathi-shree-narashiman/alphazip
공식 코드https://github.com/sweetpeach/hummingbird
공식 코드Does BERT Learn as Humans Perceive? Understanding Linguistic Styles through Lexica
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.