Source Code Plagiarism Detection (SCPD) plays an important role in maintaining fairness and academic integrity in software engineering education. Code Evaluatio...

Instructed code editing is a significant challenge for large language models (LLMs). On the EditBench benchmark, 39 of 40 evaluated models obtain a task success...

Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capture developer inte...

Editor’s note: This post is part of Into the Omniversehttps://www.nvidia.com/en-us/omniverse/news/, a series focused on how developers, 3D practitioners, and en...

Time series classification is an important analytical task across diverse domains. However, its practical application is often hindered by the scarcity of label...

!https://www.androidauthority.com/wp-content/uploads/2025/11/Gemini-3.0-Pro-hero-image-scaled.jpg Mishaal Rahman / Android Authority TL;DR - Google is working o...

Stopping criteria automatically determine when to stop an evolutionary algorithm, so as not to waste function evaluations on a stagnant population. Although sto...

!https://www.androidauthority.com/wp-content/uploads/2025/09/gemini-app-on-a-smartphone-screen-with-a-greeting-scaled.jpg TL;DR - An Android Authority teardown...

Introduction This is my first post, so here’s the punchline: the x402 agent economy is booming, but most of the services in it are garbage. I know that sounds...

!https://cdn-avatars.huggingface.co/v1/production/uploads/65df9200dc3292a8983e5017/Vs5FPVCH-VZBipV3qKTuy.png nvidia/NV-Raw2Insights-US Updated 3 days ago...

Expanded partnership overview Today, OpenAI and AWS are expanding our strategic partnership to help enterprises build using OpenAI capabilities in their AWS en...

Custom policy-learning pipelines in Spark fail for two coupled systems reasons: rowwise Python execution makes inference impractical, and driver-side candidate ...

Most developers design AI features around two axes: what the AI can do, and how it behaves technically. The missing axis is who the AI is — its character, voice...

!Cover image for Big Tech firms are accelerating AI investments and integration, while regulators and companies focus on safety and responsible adoption.https:/...

Study Overview Researchers working with data from the Internet Archive have discovered that a third of websites created since 2022 are AI‑generated, according...

The fourteenth International Conference on Learning Representations ICLR is wrapping up today in Rio de Janeiro, closing out nearly a week of presentations, deb...

April 16, 2026 In the rapidly evolving landscape of large language models LLMs, pre‑training is only the first step. To transform a base model into a specialize...

This guide shows you three ways to change which Claude model you're using with Claude Code: the quick /model command for instant changes, the --model flag for o...

The Internet of Everything (IoE) represents an evolution of the Internet of Things (IoT) by integrating people, data, processes, and things into a unified intel...

The Beagle framework, through GPU-based Genetic Programming, enables population dynamics previously unattainable (within practical time frames) by CPU-constrain...

What is a Model? A model is essentially an equation. Example y = mx + c During training, values of x and y are provided. The model learns the appropriate value...

Unified multimodal models typically rely on pretrained vision encoders and use separate visual representations for understanding and generation, creating misali...

Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods attempt to i...

Shot Boundary Detection (SBD) aims to automatically identify shot changes and divide a video into coherent shots. While SBD was widely studied in the literature...

Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and may not c...

While the optimal sample complexity of binary classification in terms of the VC dimension is well-established, determining the optimal sample complexity of mult...

In this paper, we propose a harmonized rotational gradient method, termed HRGrad, for simultaneously tackling multiscale time-dependent kinetic problems with va...

We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different solutions, e...

Specification-guided reinforcement learning (RL) provides a principled framework for encoding complex, temporally extended tasks using formal specifications suc...

Indonesian marketplace reviews mix standard vocabulary with slang, regional loanwords, numeric shorthands, and emoji, making lexicon-based sentiment tools unrel...

Segmentation models such as Segment Anything Model (SAM) and SAM2 achieve strong prompt-driven zero-shot performance. However, their training on natural images ...

Monocular RGB cameras mounted on drones are widely used for wildlife monitoring, yet most analytical pipelines remain confined to two-dimensional image space, l...

Every Transformer architecture dedicates enormous capacity to learning rich representations in semantic embedding space -- yet the rotation manifold acted upon ...

Ineffable Intelligencehttps://www.ineffable.ai/, a British AI lab founded a few months ago by former DeepMind researcher David Silver, has raised $1.1 billion a...

Hybrid sequence models that combine efficient Transformer components with linear sequence modeling blocks are a promising alternative to pure Transformers, but ...

Objective. Clinical AI documentation systems require evaluation methodologies that are clinically valid, economically viable, and sensitive to iterative changes...

Training large neural networks with data-parallel stochastic gradient descent allocates N GPU replicas to compute effectively identical updates -- a practice th...

Learning-based control techniques use data from past trajectories to control systems with uncertain dynamics. However, learning-based controllers are often comp...

Energy forecasting research faces a persistent comparability gap that makes it difficult to measure consistent progress over time. Reported accuracy gains are o...

What are Guardrails in AI? Guardrails are checks and controls added around an AI system to ensure it behaves correctly, safely, and reliably. They don’t make t...

Large language models are widely used for code generation, yet they rely on an implicit assumption that the task descriptions are sufficiently detailed and well...

Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users phrase quer...

Applications based on large language models (LLMs), such as multi-agent simulations, require population diversity among agents. We identify a pervasive failure ...

Discovering causal regularities and applying them to build functional systems--the discovery-to-application loop--is a hallmark of general intelligence, yet eva...

Agentic artificial intelligence systems promise to accelerate scientific workflows, but neuroimaging poses unique challenges: heterogeneous modalities (sMRI, fM...

Linear activation steering is a powerful approach for eliciting the capabilities of large language models and specializing their behavior using limited labeled ...

We propose Noise-Based Spectral Embedding (NBSE), a physics-informed framework for selecting informative features from high-dimensional data without greedy sear...

While Large Language Models (LLMs) have increasingly assisted in historical tasks such as text processing, their capacity for professional-level historical reas...