[Code Debugging Challenge] Can you spot the 'trap' in this PyTorch code? A thought experiment on LLM implementation learned from CS336

Introduction: 'Bugs that don't throw errors' are the most terrifyingWhen implementing LLMs (Large Language Models) in Python ...
BIOENGINEER

New Loss Function Helps AI Learn From Flawed Labels

The practical significance of the RECE approach becomes clearer when viewed against the broader economics of dataset ...
BIOENGINEER

Hybrid CNN-ViT Model With Triple Loss Boosts Image Search Accuracy

Image search is quietly becoming one of the most demanding tests of artificial intelligence. When a user submits a photo and asks a system to find visually similar images across a database of ...
blog.csdn

PaddleSeg Loss Functions Complete Guide: Cross Entropy, Lovasz, OHEM, Dice and More

PaddleSeg 内置了一套完整、可插拔的损失函数库（paddleseg.models.losses），覆盖从基础交叉熵到 OHEM 难样本挖掘、Lovasz 系列、Dice、语义连通性（SCL）等语义分割常用损失。本指南以官方文档 losses_en ...
blog.csdn

Loss Functions：Logistic Loss、Cross Entropy 与 Hinge Loss

原创 最新推荐文章于 2026-09-04 19:45:01 发布 · 234 阅读 在机器学习和深度学习中，损失函数（Loss Function） 用来衡量模型预测结果与真实答案之间的差距。 训练模型的过程，本质上就是不断调整 ...
bilibili

【面试高频】InfoNCE Loss 和 Cross Entropy Loss 有什么区别？对比学习核心损失全解析

交叉熵和 InfoNCE 都是让模型学会「分辨」，但用的场景截然不同，核心分歧藏在一个词：对比。本期从原理到特征分布讲清： Cross Entropy（交叉熵）：分类任务里最常用的有监督损失，依赖真实 ...
Frontiers

TCMB: cross-model multi-level cross-attention network with Taylor-based loss for multimodal fake news detection

The rapid spread of misinformation across social media platforms, websites, and online communication channels has made fake news detection a critical task in the digital era. Although various ...
PNAS

ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling

The increasing availability of complex, heterogeneous datasets poses significant challenges for traditional data-driven methods, which often assume data homogeneity and fail to account for internal ...