Efficiency Collection

◆

◆

◆

◆

🔥Fire

★★★★

“PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）”

◆

◆

◆

◆

🌊Water

★★

“An Efficient Enterprise-class Container Engine”

◆

◆

◆

◆

⚔️Fighting

★★

“💌A tiny (995KB) but mighty timer in **pure C** ! — almost no memory usage!❤️‍🔥 Supports clock, countdown, stopwatch, Pomodoro, and fully customizable tray animations (GIFs, CPU/Mem%) 💘 Don't be shy, join here🧸: https://discord.com/invite/W3tW2gtp6g”

◆

◆

◆

◆

🔮Psychic

★★

“Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)”

◆

◆

◆

◆

🔮Psychic

★★

“This is a collection of our NAS and Vision Transformer work.”

◆

◆

◆

◆

🔮Psychic

★★

“Rigourous evaluation of LLM-synthesized code - NeurIPS 2023 & COLM 2024”

◆

◆

◆

◆

📦Normal

★★

“An efficiency tool that provides various functions by enhancing the Caps Lock key into a modifier key.”

◆

◆

◆

◆

🔮Psychic

★★

“An ultra fast cross-platform multiple screenshots module in pure Python using ctypes.”

◆

◆

◆

◆

💎Aqua

★★

“Pomodoro Logger :clock930: -- When a time tracker meets Pomodoro and Kanban board”

◆

◆

◆

◆

⚙️Steel

★★

“terminal-based personal organizer”

◆

◆

◆

◆

🔮Psychic

★★

“[EMNLP'25] s3 - ⚡ Efficient & Effective Search Agent Training via RL for RAG (RLVR for Search with Minimal Data)”

◆

◆

◆

◆

📦Normal

★★

“[TMLR 2025] Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models”

◆

◆

◆

◆

💎Aqua

★★

“A command launcher for Chrome”

◆

◆

◆

◆

🔮Psychic

★★

“[ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning”

◆

◆

◆

◆

🔮Psychic

★★

“[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution”

◆

◆

◆

◆

🔮Psychic

★★

“Easy-to-use data analysis / manipulation framework for humans”

◆

◆

◆

◆

🔥Fire

★★

“An app launcher && efficiency tool ”

◆

◆

◆

◆

📦Normal

★★

“Official implementation of Würstchen: Efficient Pretraining of Text-to-Image Models”