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/sisinflab/ducho

공식 코드

Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation

https://github.com/sisinflab/formal-multimod-rec

공식 코드

Formalizing Multimedia Recommendation through Multimodal Deep Learning

https://github.com/sisinflab/llm-memoryinspector

공식 코드

Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M

https://github.com/sislab-unitn/dyknow

공식 코드

DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs

https://github.com/sjmeis/mldp

공식 코드

A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking The Privacy-Utility Trade-off

https://github.com/sjtu-omniagent/vocalbench

공식 코드

VocalBench: Benchmarking the Vocal Conversational Abilities for Speech Interaction Models

https://github.com/skelemoa/quovadis

공식 코드

Quo Vadis, Skeleton Action Recognition ?

https://github.com/sktsherlock/atg

공식 코드

When Graph meets Multimodal: Benchmarking on Multimodal Attributed Graphs Learning

https://github.com/slavovlab/scp_recommendations

공식 코드

Initial recommendations for performing, benchmarking, and reporting single-cell proteomics experiments

https://github.com/slds-lmu/qdo_yahpo

공식 코드

A Collection of Quality Diversity Optimization Problems Derived from Hyperparameter Optimization of Machine Learning Models

https://github.com/slyipae1/MedBookVQA

공식 코드

MedBookVQA: A Systematic and Comprehensive Medical Benchmark Derived from Open-Access Book

https://github.com/sm4da/qemfi

공식 코드

QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules

https://github.com/smartyfh/llm-uncertainty-bench

공식 코드

Benchmarking LLMs via Uncertainty Quantification

https://github.com/sming256/OpenTAD

공식 코드

OpenTAD: A Unified Framework and Comprehensive Study of Temporal Action Detection

https://github.com/smpl-env/smpl

공식 코드

SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments

https://github.com/smplbody/hmr-benchmarks

공식 코드

Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms

https://github.com/snap-research/r2l

공식 코드

SCoDA: Domain Adaptive Shape Completion for Real Scans

https://github.com/snap-stanford/mlagentbench

공식 코드

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

https://github.com/snap-stanford/stark

공식 코드

STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases

https://github.com/snousias/Revisiting-Content-Based-Audio-Classification-for-Asthma-Medication-Adherence

공식 코드

AI-enabled Sound Pattern Recognition on Asthma Medication Adherence: Evaluation with the RDA Benchmark Suite

https://github.com/social-ai-studio/hatred

공식 코드

Decoding the Underlying Meaning of Multimodal Hateful Memes

https://github.com/socialfoundations/training-on-the-test-task

공식 코드

Training on the Test Task Confounds Evaluation and Emergence

https://github.com/soda-inria/retrieve-merge-predict

공식 코드

Retrieve, Merge, Predict: Augmenting Tables with Data Lakes

https://github.com/soda-inria/yadl

공식 코드

Retrieve, Merge, Predict: Augmenting Tables with Data Lakes

https://github.com/solirinai/geobenchx

공식 코드

GeoBenchX: Benchmarking LLMs for Multistep Geospatial Tasks

https://github.com/songrise/mllm4art

공식 코드

Multimodal LLMs Can Reason about Aesthetics in Zero-Shot

https://github.com/sonyresearch/coala

공식 코드

COALA: A Practical and Vision-Centric Federated Learning Platform

https://github.com/soombit-ai/chexgpt

공식 코드

CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling

https://github.com/sougata-ub/llms_for_ionic_liquids

공식 코드

From Knowledge to Reasoning: Evaluating LLMs for Ionic Liquids Research in Chemical and Biological Engineering

https://github.com/soumyabrata/ehr-features

공식 코드

A predictive analytics approach for stroke prediction using machine learning and neural networks

https://github.com/soundclim/anuraset

공식 코드

AnuraSet: A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring

https://github.com/spacelearner/graph-gpt

공식 코드

GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

https://github.com/spaghettiSystems/serval

공식 코드

SER Evals: In-domain and Out-of-domain Benchmarking for Speech Emotion Recognition

https://github.com/spalabucr/pategan-audit

공식 코드

The Elusive Pursuit of Reproducing PATE-GAN: Benchmarking, Auditing, Debugging

https://github.com/sparisi/visit-value-explore

공식 코드

Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning

https://github.com/spcl/mrag

공식 코드

Multi-Head RAG: Solving Multi-Aspect Problems with LLMs

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