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/indobenchmark/indonlu

공식 코드

IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding

https://github.com/indyfree/CARLA

공식 코드

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

https://github.com/infiagent/infiagent

공식 코드

InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks

https://github.com/infinigence/lveval

공식 코드

LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K

https://github.com/inigoval/fixmatch

공식 코드

Radio Galaxy Zoo: Using semi-supervised learning to leverage large unlabelled data-sets for radio galaxy classification under data-set shift

https://github.com/ink7-sudo/dependeval

공식 코드

DependEval: Benchmarking LLMs for Repository Dependency Understanding

https://github.com/inm-6/bennch

공식 코드

A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations

https://github.com/innodatalabs/innodata-llm-safety

공식 코드

Benchmarking Llama2, Mistral, Gemma and GPT for Factuality, Toxicity, Bias and Propensity for Hallucinations

https://github.com/inouye-lab/feddg_benchmark

공식 코드

Benchmarking Algorithms for Federated Domain Generalization

https://github.com/inspirai/wilderness-scavenger

공식 코드

WILD-SCAV: Benchmarking FPS Gaming AI on Unity3D-based Environments

https://github.com/instadeepai/compass

공식 코드

Combinatorial Optimization with Policy Adaptation using Latent Space Search

https://github.com/instadeepai/debatellm

공식 코드

Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs

https://github.com/intelligent-computing-lab-yale/quanitzation-aware-snn-training-and-hardware-evaluation-for-imc-architectures

공식 코드

SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks

https://github.com/interaction-lab/hribench

공식 코드

HRIBench: Benchmarking Vision-Language Models for Real-Time Human Perception in Human-Robot Interaction

https://github.com/interactivenlp-team/rolellm-public

공식 코드

RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models

https://github.com/intmegroup/lmm4lmm

공식 코드

LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs

https://github.com/intmegroup/love

공식 코드

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation

https://github.com/iocuydi/amharic-llama-llava

공식 코드

Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages

https://github.com/ioverho/misinfo-general

공식 코드

Yesterday's News: Benchmarking Multi-Dimensional Out-of-Distribution Generalisation of Misinformation Detection Models

https://github.com/ipolharvard/ethos-ares

공식 코드

Foundation Model of Electronic Medical Records for Adaptive Risk Estimation

https://github.com/ipouyall/benchmarking_chatgpt_for_persian

공식 코드

Benchmarking Large Language Models for Persian: A Preliminary Study Focusing on ChatGPT

https://github.com/irmlma/mobility-simulation-cdpm

공식 코드

Synthetic location trajectory generation using categorical diffusion models

https://github.com/is2lab/s-eval

공식 코드

S-Eval: Towards Automated and Comprehensive Safety Evaluation for Large Language Models

https://github.com/isayevlab/geom-drugs-3dgen-evaluation

공식 코드

GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation

https://github.com/isle-dev/ecbd

공식 코드

ECBD: Evidence-Centered Benchmark Design for NLP

https://github.com/itssmutnuri/gnnvariants

공식 코드

Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks

https://github.com/ivalab/Benchmarking_SLAM

공식 코드

Characterizing SLAM Benchmarks and Methods for the Robust Perception Age

https://github.com/ivan-chai/hotpp-benchmark

공식 코드

HoTPP Benchmark: Are We Good at the Long Horizon Events Forecasting?

https://github.com/iwan-rg/saudi_privacy_policy

공식 코드

The Saudi Privacy Policy Dataset

https://github.com/izaznov/adamz

공식 코드

AdamZ: An Enhanced Optimisation Method for Neural Network Training

https://github.com/j-adamczyk/apis_tox_dataset

공식 코드

ApisTox: a new benchmark dataset for the classification of small molecules toxicity on honey bees

https://github.com/j-bac/scikit-dimension

공식 코드

Scikit-dimension: a Python package for intrinsic dimension estimation

https://github.com/jaabmar/kernel-test-bias

공식 코드

Detecting critical treatment effect bias in small subgroups

https://github.com/jacobfulano/cyclic-learning-rate-schedules

공식 코드

Fast Benchmarking of Accuracy vs. Training Time with Cyclic Learning Rates

https://github.com/jadie1/medseguq

공식 코드

Benchmarking Scalable Epistemic Uncertainty Quantification in Organ Segmentation

https://github.com/jahanpd/missingness

공식 코드

Dealing with missing data using attention and latent space regularization

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