Papers with Code 아카이브

Benchmarking

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

2

보존된 평가 기록

2

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/mbzuai-nlp/urdufactcheck

공식 코드

UrduFactCheck: An Agentic Fact-Checking Framework for Urdu with Evidence Boosting and Benchmarking

https://github.com/mbzuai-oryx/video-llava

공식 코드

PG-Video-LLaVA: Pixel Grounding Large Video-Language Models

https://github.com/mc-eiu/mc-eiu

공식 코드

Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset

https://github.com/mcg-nju/sorce

공식 코드

SORCE: Small Object Retrieval in Complex Environments

https://github.com/mcleish7/clrs4lm

공식 코드

Benchmarking ChatGPT on Algorithmic Reasoning

https://github.com/mdabbah/COOD_benchmarking

공식 코드

A framework for benchmarking class-out-of-distribution detection and its application to ImageNet

https://github.com/mehmetaygun/4d-pls

공식 코드

4D Panoptic LiDAR Segmentation

https://github.com/mehrzadshm/built-bench-paper

공식 코드

Benchmarking pre-trained text embedding models in aligning built asset information

https://github.com/melanibe/failure_detection_benchmark

공식 코드

Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

https://github.com/mengfeidu/embspatial-bench

공식 코드

EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models

https://github.com/menik1126/TRIGO

공식 코드

TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models

https://github.com/metaagentx/opencaptchaworld

공식 코드

Open CaptchaWorld: A Comprehensive Web-based Platform for Testing and Benchmarking Multimodal LLM Agents

https://github.com/metacopilot/dseval

공식 코드

Benchmarking Data Science Agents

https://github.com/metadriverse/metadrive

공식 코드

MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning

https://github.com/metaevo/q-mamba

공식 코드

Meta-Black-Box-Optimization through Offline Q-function Learning

https://github.com/metaslam/alto

공식 코드

ALTO: A Large-Scale Dataset for UAV Visual Place Recognition and Localization

https://github.com/mever-team/sidbench

공식 코드

SIDBench: A Python Framework for Reliably Assessing Synthetic Image Detection Methods

https://github.com/mgbukov/rl_disentangle

공식 코드

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations

https://github.com/mgwillia/unsupervised-analysis

공식 코드

Beyond Supervised vs. Unsupervised: Representative Benchmarking and Analysis of Image Representation Learning

https://github.com/mi2datalab/agg2exp

공식 코드

Aggregated Attributions for Explanatory Analysis of 3D Segmentation Models

https://github.com/miaoxiong2320/llm-uncertainty

공식 코드

Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

https://github.com/mic-dkfz/foundation-models-for-cbmir

공식 코드

Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology

https://github.com/mic-dkfz/napari-nninteractive

공식 코드

nnInteractive: Redefining 3D Promptable Segmentation

https://github.com/mic-dkfz/nninteractive

공식 코드

nnInteractive: Redefining 3D Promptable Segmentation

https://github.com/mic-dkfz/nnssl

공식 코드

An OpenMind for 3D medical vision self-supervised learning

https://github.com/miccunifi/circo

공식 코드

iSEARLE: Improving Textual Inversion for Zero-Shot Composed Image Retrieval

https://github.com/micdoh/XLRON

공식 코드

Reinforcement Learning for Dynamic Resource Allocation in Optical Networks: Hype or Hope?

https://github.com/michaelsaxon/T2IScoreScore

공식 코드

Who Evaluates the Evaluations? Objectively Scoring Text-to-Image Prompt Coherence Metrics with T2IScoreScore (TS2)

https://github.com/michaelsaxon/cococrola

공식 코드

Multilingual Conceptual Coverage in Text-to-Image Models

https://github.com/michalspiegel/imgtb

공식 코드

IMGTB: A Framework for Machine-Generated Text Detection Benchmarking

https://github.com/microsoft/AirSim-NeurIPS2019-Drone-Racing

공식 코드

AirSim Drone Racing Lab

https://github.com/microsoft/BIPIA

공식 코드

Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models

https://github.com/microsoft/ContextualSP

공식 코드

MultiSpider: Towards Benchmarking Multilingual Text-to-SQL Semantic Parsing

https://github.com/microsoft/JARVIS

공식 코드

TaskBench: Benchmarking Large Language Models for Task Automation

https://github.com/microsoft/VISOR

공식 코드

Benchmarking Spatial Relationships in Text-to-Image Generation

https://github.com/microsoft/deepspeed-mii

공식 코드

DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.