Posts

All the articles I've posted.

• ASURA-FDPS-ML: Star-by-star Galaxy Simulations Accelerated by Surrogate Modeling for Supernova Feedback

  Published: 15 May, 2025 |  at  11:07 AM

  

  95.02 🤔

  This paper introduces ASURA-FDPS-ML, a framework that accelerates high-resolution galaxy simulations by using a machine learning surrogate model for supernova feedback in dense regions, achieving a fourfold speedup while maintaining comparable morphological and outflow characteristics to direct simulations, despite some discrepancies in momentum at higher altitudes.

• Label-efficient Single Photon Images Classification via Active Learning

  Published: 16 May, 2025 |  at  11:11 AM

  

  95.02 🤔

  This paper proposes an active learning framework for single-photon image classification that uses imaging condition-aware synthetic augmentation and a diversity-guided uncertainty-inconsistency sampling strategy to achieve high accuracy (97% on synthetic, 90.63% on real-world data) with significantly fewer labeled samples (1.5% and 8%, respectively) compared to baselines.

• Towards Safer Pretraining: Analyzing and Filtering Harmful Content in Webscale datasets for Responsible LLMs

  Published: 8 May, 2025 |  at  11:07 AM

  

  94.57 🤔

  This paper proposes a three-dimensional taxonomy and develops TTP and HarmFormer tools to filter harmful content from web-scale LLM pretraining datasets, revealing significant toxicity prevalence and persistent safety gaps through benchmarks like HAVOC.

• A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone

  Published: 21 May, 2025 |  at  11:14 AM

  

  94.56 🤔

  本文提出低秩克隆（LRC）方法，通过低秩投影矩阵和激活克隆实现从大型语言模型到小型语言模型的高效知识蒸馏，仅用10-20B tokens训练即可媲美或超越训练数据量达数万亿tokens的模型，显著提升训练效率。

• Learning to Drift in Extreme Turning with Active Exploration and Gaussian Process Based MPC

  Published: 15 May, 2025 |  at  11:06 AM

  

  94.41 🤔

  This paper introduces AEDGPR-MPC, a framework combining Model Predictive Control with Gaussian Process Regression and active exploration to correct vehicle model mismatches, achieving significant reductions in lateral error (up to 52.8% in simulation, 36.7% in RC car tests) and velocity tracking RMSE during extreme cornering drift control.