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Building an Amazon Advertising ROI Optimization System with Python
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AI — Latest Models & Research
AI
Building an Amazon Advertising ROI Optimization System with Python
Amazon advertising in 2026 is a data game. Top sellers have reduced their ACoS (Advertising Cost of...
DEV Community
AI
🧼 Beginner-Friendly Guide 'Minimum Pair Removal to Sort Array II' - LeetCode 3510 (C++, Python, JavaScript)
Sorting an array usually involves swapping elements, but what if you had to combine them instead?...
DEV Community
AI
Predicting the Spike: Building a CGM Warning System with Transformers and PyTorch Forecasting
In the world of Time Series Forecasting, managing non-stationary data like Continuous Glucose...
DEV Community
AI
Implicit Intent Routing
``I’ve been working on refining the UX for "Hybrid Agents"—assistants that need to switch seamlessly...
DEV Community
AI
Stop Using Frameworks Blindly: Build Your Own Python Web Server from Scratch
If you’ve ever built a web application using Flask or Django, you know the magic is instant. You run...
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AI
Why Can't I Open My Drawer? Mitigating Object-Driven Shortcuts in Zero-Shot Compositional Action Recognition
We study Compositional Video Understanding (CVU), where models must recognize verbs and objects and compose them to generalize to unseen combinations. We find that existing Zero-Shot Compositional Action Recognition (ZS-CAR) models fail primarily due to an overlooked failure mode: object-driven verb shortcuts. Through systematic analysis, we show that this behavior arises from two intertwined fact
arXiv
AI
PyraTok: Language-Aligned Pyramidal Tokenizer for Video Understanding and Generation
Discrete video VAEs underpin modern text-to-video generation and video understanding systems, yet existing tokenizers typically learn visual codebooks at a single scale with limited vocabularies and shallow language supervision, leading to poor cross-modal alignment and zero-shot transfer. We introduce PyraTok, a language-aligned pyramidal tokenizer that learns semantically structured discrete lat
arXiv
AI
LLM-in-Sandbox Elicits General Agentic Intelligence
We introduce LLM-in-Sandbox, enabling LLMs to explore within a code sandbox (i.e., a virtual computer), to elicit general intelligence in non-code domains. We first demonstrate that strong LLMs, without additional training, exhibit generalization capabilities to leverage the code sandbox for non-code tasks. For example, LLMs spontaneously access external resources to acquire new knowledge, leverag
arXiv
AI
Counterfactual Training: Teaching Models Plausible and Actionable Explanations
We propose a novel training regime termed counterfactual training that leverages counterfactual explanations to increase the explanatory capacity of models. Counterfactual explanations have emerged as a popular post-hoc explanation method for opaque machine learning models: they inform how factual inputs would need to change in order for a model to produce some desired output. To be useful in real
arXiv
AI
Provable Robustness in Multimodal Large Language Models via Feature Space Smoothing
Multimodal large language models (MLLMs) exhibit strong capabilities across diverse applications, yet remain vulnerable to adversarial perturbations that distort their feature representations and induce erroneous predictions. To address this vulnerability, we propose the Feature-space Smoothing (FS) and theoretically prove that FS offers certified robustness on the feature representations of MLLMs
arXiv
AI
A Rolling-Space Branch-and-Price Algorithm for the Multi-Compartment Vehicle Routing Problem with Multiple Time Windows
This paper investigates the multi-compartment vehicle routing problem with multiple time windows (MCVRPMTW), an extension of the classical vehicle routing problem with time windows that considers vehicles equipped with multiple compartments and customers requiring service across several delivery time windows. The problem incorporates three key compartment-related features: (i) compartment flexibil
arXiv
AI
My Two Best Teammates Have Four Paws. And They Keep Me Sane While Coding
"11 years with Kacia, 1.5 years with surprise Lusia. The dogs who taught me loyalty, forced breaks,...
DEV Community