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Data-free Knowledge Distillation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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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/taowangzj/llformer

공식 코드

Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method

https://github.com/taozhen1110/cudrt

공식 코드

Towards Reliable Detection of LLM-Generated Texts: A Comprehensive Evaluation Framework with CUDRT

https://github.com/tapilot-crossing/tapilot_code

공식 코드

Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

https://github.com/tareknaous/readme

공식 코드

ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability Assessment

https://github.com/taskography/taskography

공식 코드

TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs

https://github.com/taucompling/bliss

공식 코드

Benchmarking Neural Network Generalization for Grammar Induction

https://github.com/teddy-xionggz/medrag

공식 코드

Benchmarking Retrieval-Augmented Generation for Medicine

https://github.com/teddy-xionggz/mirage

공식 코드

Benchmarking Retrieval-Augmented Generation for Medicine

https://github.com/tekdogan/iccbdc-21

공식 코드

Benchmarking Apache Spark and Hadoop MapReduce on Big Data Classification

https://github.com/tencent-ailab/DrugOOD

공식 코드

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations

https://github.com/tencent-ailab/rlogist

공식 코드

RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning

https://github.com/tencent-alchemy/Alchemy

공식 코드

Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models

https://github.com/tensorflow/cleverhans

공식 코드

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

https://github.com/terarachang/memdata

공식 코드

Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks

https://github.com/terarachang/mempi

공식 코드

Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks

https://github.com/ternaus/robot-surgery-segmentation

공식 코드

2017 Robotic Instrument Segmentation Challenge

https://github.com/testing-cs/codes

공식 코드

CodeS: Towards Code Model Generalization Under Distribution Shift

https://github.com/testing-cs/codes-distribution-shift-benchmark-datasets

공식 코드

CodeS: Towards Code Model Generalization Under Distribution Shift

https://github.com/testzer0/ambiqt

공식 코드

Benchmarking and Improving Text-to-SQL Generation under Ambiguity

https://github.com/the-ai-alliance/geo-bench-vlm

공식 코드

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks

https://github.com/the-finai/fino1

공식 코드

Fino1: On the Transferability of Reasoning Enhanced LLMs to Finance

https://github.com/theagentcompany/experiments

공식 코드

TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

https://github.com/theagentcompany/theagentcompany

공식 코드

TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

https://github.com/theislab/trVAE

공식 코드

Conditional out-of-sample generation for unpaired data using trVAE

https://github.com/thended32/analyzingfeatureextractors

공식 코드

Analyzing the Feature Extractor Networks for Face Image Synthesis

https://github.com/thepanlab/NACHOS

공식 코드

Integration of nested cross-validation, automated hyperparameter optimization, high-performance computing to reduce and quantify the variance of test performance estimation of deep learning models

https://github.com/thinklab-sjtu/bench2drivezoo

공식 코드

Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving

https://github.com/thinklab-sjtu/predictiveco-benchmark

공식 코드

Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime

https://github.com/thiviyant/intelligraphs

공식 코드

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation

https://github.com/thomasehuber/s5-rf

공식 코드

Scaling Up Resonate-and-Fire Networks for Fast Deep Learning

https://github.com/thu-coai/autodetect

공식 코드

AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language Models

https://github.com/thu-coai/characterbench

공식 코드

CharacterBench: Benchmarking Character Customization of Large Language Models

https://github.com/thu-coai/complexbench

공식 코드

Benchmarking Complex Instruction-Following with Multiple Constraints Composition

https://github.com/thu-keg/agentif

공식 코드

AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

https://github.com/thu-keg/kola

공식 코드

KoLA: Carefully Benchmarking World Knowledge of Large Language Models

https://github.com/thu-keg/rm-bench

공식 코드

RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style

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