· ai
[Paper] Pre-train to Gain: Robust Learning Without Clean Labels
Training deep networks with noisy labels leads to poor generalization and degraded accuracy due to overfitting to label noise. Existing approaches for learning ...
-
- · software
[Paper] Train While You Fight -- Technical Requirements for Advanced Distributed Learning Platforms
'Train While You Fight' (TWYF) advocates for continuous learning that occurs during operations, not just before or after. This paper examines the technical requ...
- · software
[Paper] Translating Large-Scale C Repositories to Idiomatic Rust
Existing C to Rust translation techniques fail to balance quality and scalability: transpilation-based approaches scale to large projects but produce code with ...
- · ai
[Paper] Ranking-Enhanced Anomaly Detection Using Active Learning-Assisted Attention Adversarial Dual AutoEncoders
Advanced Persistent Threats (APTs) pose a significant challenge in cybersecurity due to their stealthy and long-term nature. Modern supervised learning methods ...
- · ai
[Paper] LLMs for Automated Unit Test Generation and Assessment in Java: The AgoneTest Framework
Unit testing is an essential but resource-intensive step in software development, ensuring individual code units function correctly. This paper introduces Agone...
- · devops
[Paper] Interactive Visualization of Proof-of-Work Consensus Protocol on Raspberry Pi
We describe a prototype of a fully capable Ethereum Proof-of-Work (PoW) blockchain network running on multiple Raspberry Pi (RPi) computers. The prototype is ea...
- · ai
[Paper] NNGPT: Rethinking AutoML with Large Language Models
Building self-improving AI systems remains a fundamental challenge in the AI domain. We present NNGPT, an open-source framework that turns a large language mode...
- · devops
[Paper] Parallel simulation and adaptive mesh refinement for 3D elastostatic contact mechanics problems between deformable bodies
Parallel implementation of numerical adaptive mesh refinement (AMR)strategies for solving 3D elastostatic contact mechanics problems is an essential step toward...
- · ai
[Paper] QiMeng-Kernel: Macro-Thinking Micro-Coding Paradigm for LLM-Based High-Performance GPU Kernel Generation
Developing high-performance GPU kernels is critical for AI and scientific computing, but remains challenging due to its reliance on expert crafting and poor por...
- · devops
[Paper] SwitchDelta: Asynchronous Metadata Updating for Distributed Storage with In-Network Data Visibility
Distributed storage systems typically maintain strong consistency between data nodes and metadata nodes by adopting ordered writes: 1) first installing data; 2)...
- · ai
[Paper] Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning
Asynchronous federated learning (FL) has recently gained attention for its enhanced efficiency and scalability, enabling local clients to send model updates to ...
- · ai
[Paper] ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models
Federated learning (FL) has been extensively studied as a privacy-preserving training paradigm. Recently, federated block coordinate descent scheme has become a...