Papers with Code 아카이브

Data-free Knowledge Distillation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 1
평가표: 2
보존된 평가 기록: 8

코드

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

https://github.com/likaixin2000/mmcode

공식 코드

MMCode: Benchmarking Multimodal Large Language Models for Code Generation with Visually Rich Programming Problems

https://github.com/likyoo/open-cd

공식 코드

Open-CD: A Comprehensive Toolbox for Change Detection

https://github.com/liminxian/DukeMTMC-SI-Tracklet

공식 코드

Unsupervised Tracklet Person Re-Identification

https://github.com/lin-rany/codeIF

공식 코드

CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation

https://github.com/lina-usc/jansen-rit-model-benchmarking-deep-learning

공식 코드

Deep Jansen-Rit Parameter Inference for Model-Driven Analysis of Brain Activity

https://github.com/lingjuanlv/FPPDL

공식 코드

Towards Fair and Privacy-Preserving Federated Deep Models

https://github.com/linglongqian/csai

공식 코드

Knowledge Enhanced Conditional Imputation for Healthcare Time-series

https://github.com/lingxitong/CAMELYON-PLUS-BENCHMARK

공식 코드

Towards a Comprehensive Benchmark for Pathological Lymph Node Metastasis in Breast Cancer Sections

https://github.com/linhaowei1/clog

공식 코드

CLoG: Benchmarking Continual Learning of Image Generation Models

https://github.com/linhaowei1/kumo

공식 코드

Generative Evaluation of Complex Reasoning in Large Language Models

https://github.com/linxins97/nlpbench

공식 코드

NLPBench: Evaluating Large Language Models on Solving NLP Problems

https://github.com/linzhiqiu/t2v_metrics

공식 코드

GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

https://github.com/liqinye/sidyp

공식 코드

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement

https://github.com/lishangyu-hkust/osvbench

공식 코드

OSVBench: Benchmarking LLMs on Specification Generation Tasks for Operating System Verification

https://github.com/littlepenguin89106/mgcac

공식 코드

A Recipe for CAC: Mosaic-based Generalized Loss for Improved Class-Agnostic Counting

https://github.com/liu-hy/genotex

공식 코드

GenoTEX: An LLM Agent Benchmark for Automated Gene Expression Data Analysis

https://github.com/liu-yushan/PoLo

공식 코드

Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs

https://github.com/liu00222/open-prompt-injection

공식 코드

Formalizing and Benchmarking Prompt Injection Attacks and Defenses

https://github.com/liudan193/Fairness-Benchmark-for-Face-Forgery-Detection

공식 코드

Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and Evaluations

https://github.com/liugangcode/Llamole

공식 코드

Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning

https://github.com/liukidar/pcax

공식 코드

Benchmarking Predictive Coding Networks -- Made Simple

https://github.com/liuyuaa/SurvUnc

공식 코드

SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis

https://github.com/liuzey/CheckGPT

공식 코드

On the Detectability of ChatGPT Content: Benchmarking, Methodology, and Evaluation through the Lens of Academic Writing

https://github.com/liuzuxin/dsrl

공식 코드

Datasets and Benchmarks for Offline Safe Reinforcement Learning

https://github.com/liuzuxin/fsrl

공식 코드

Datasets and Benchmarks for Offline Safe Reinforcement Learning

https://github.com/liuzuxin/osrl

공식 코드

Datasets and Benchmarks for Offline Safe Reinforcement Learning

https://github.com/livingingroups/animal2vec

공식 코드

animal2vec and MeerKAT: A self-supervised transformer for rare-event raw audio input and a large-scale reference dataset for bioacoustics

https://github.com/lize-alberts/llm_prag_benchmark

공식 코드

CURATe: Benchmarking Personalised Alignment of Conversational AI Assistants

https://github.com/ljcleo/agent_sense

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AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios

https://github.com/ljrprocc/datafree

공식 코드

Dynamic Data-Free Knowledge Distillation by Easy-to-Hard Learning Strategy

https://github.com/ljungang/rtv-bench

공식 코드

RTV-Bench: Benchmarking MLLM Continuous Perception, Understanding and Reasoning through Real-Time Video

https://github.com/lkopf/cosy

공식 코드

CoSy: Evaluating Textual Explanations of Neurons

https://github.com/ll0ruc/AutoMIR

공식 코드

AutoMIR: Effective Zero-Shot Medical Information Retrieval without Relevance Labels

https://github.com/llcresearch/genception

공식 코드

GenCeption: Evaluate Multimodal LLMs with Unlabeled Unimodal Data

https://github.com/llllly26/complexbench-edit

공식 코드

ComplexBench-Edit: Benchmarking Complex Instruction-Driven Image Editing via Compositional Dependencies

https://github.com/llm-eval-mental-health/counselbench

공식 코드

CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmark of Large Language Models in Mental Health Counseling

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