Robotics foundation models have demonstrated strong capabilities in executing natural language instructions across diverse tasks and environments. However, they...
Handling gender across languages remains a persistent challenge for Machine Translation (MT) and Large Language Models (LLMs), especially when translating from ...
While Large Language Models achieve state-of-the-art results across a wide range of NLP tasks, they remain prone to systematic biases. Among these, gender bias ...
Extending language models to video introduces two challenges: representation, where existing methods rely on lossy approximations, and long-context, where capti...
Rapid adaptation in complex control systems remains a central challenge in reinforcement learning. We introduce a framework in which policy and value functions ...
Converting pretrained attention modules such as grouped-query attention (GQA) into multi-head latent attention (MLA) can improve expressivity without increasing...
In multilingual pretraining, the test loss of a pretrained model is heavily influenced by the proportion of each language in the pretraining data, namely the la...
Large language models (LLMs) exhibit latent multi-token prediction (MTP) capabilities despite being trained solely for next-token generation. We propose a simpl...
Overview The artificial intelligence hype remains strong among corporate leaders and venture capitalists, who view the technology as a way to cut payroll costs...
We consider a variant of sequential testing by betting where, at each time step, the statistician is presented with multiple data sources (arms) and obtains dat...
Large language models (LLMs) contain billions of parameters, yet many exact values are not essential. We show that what matters most is the relative rank of wei...
As large language models (LLMs) are deployed in multilingual settings, their safety behavior in culturally diverse, low-resource languages remains poorly unders...
Understanding the distance between human languages is central to linguistics, anthropology, and tracing human evolutionary history. Yet, while linguistics has l...
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Large language models (LLMs) and AI agents are increasingly integrated into enterprise systems to access internal databases and generate context-aware responses...
Overview Artificial intelligence models are multiplying fast, and competition is stiff. With so many players crowding the space, which one will be the best — a...
Understanding when learning is statistically possible yet computationally hard is a central challenge in high-dimensional statistics. In this work, we investiga...
Methodology bugs in scientific Python code produce plausible but incorrect results that traditional linters and static analysis tools cannot detect. Several res...
Post training quantization is essential for deploying large language models (LLMs) on resource constrained hardware, yet state of the art methods enforce unifor...
Large language models (LLMs) are trained through multi-stage pipelines over heterogeneous data sources, yet developers lack a principled way to pinpoint the spe...
Large Language Models (LLMs) have achieved unprecedented fluency but remain susceptible to 'hallucinations' - the generation of factually incorrect or ungrounde...
Overview A powerful, anonymous AIhttps://mashable.com/category/artificial-intelligence model quietly appeared on the developer platform OpenRouter on March 11....
A prerequisite for coding agents to perform tasks on large repositories is code localization - the identification of relevant files, classes, and functions to w...
Multimodal Automated Program Repair (MAPR) extends traditional program repair by requiring models to jointly reason over source code, textual issue descriptions...
⚠️ Full disclosure: This post was written by Mupeng, an AI agent built on OpenClawhttps://github.com/openclaw/openclaw. My human Jong‑hyun Jung, CEO of MUFI rev...
!NVIDIA GTC 2026: Live Updates on What’s Next in AIhttps://blogs.nvidia.com/wp-content/uploads/2026/03/26gtc-blog-1920x1080-DEB35146-300x169.jpeg NVIDIA GTC 202...
Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relative to infer...
The biggest shift in agent design over the past year has been context engineering rather than improved models Most of the published guidance focuses on codebas...
ChatGPT has 700 million weekly active users. It's the default AI for most of the planet. But if you're a developer choosing your daily driver based on popularit...
This article introduces and substantiates the concept of Neuro-Linguistic Integration (NLI), a novel paradigm for human-technology interaction where Large Langu...
Lossless model compression holds tremendous promise for alleviating the memory and bandwidth bottlenecks in bit-exact Large Language Model (LLM) serving. Howeve...
The audit report arrived at 2:47 am, just after I’d triggered a test run out of habit. It contained a score, a six‑dimension breakdown, and a remediation plan w...
A coding agent can bootstrap itself. Starting from a 926-word specification and a first implementation produced by an existing agent (Claude Code), a newly gene...
Key Points from Nicholas Burns The United States and China “are the two largest emitters of carbon in the world,” said Nicholas Burnshttps://www.hks.harvard.ed...
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Backpropagation has enabled modern deep learning but is difficult to realize as an online, fully distributed hardware learning system due to global error propag...
The Problem If you've been building with AI agents like Claude Code, you've probably encountered these problems: - Context loss – Starting a new session wipes...
Lance Martin at LangChain published a framework for context engineering with four operations: Write, Select, Compress, and Isolate. Each operation has a failure...
Claude Desktop can browse the web and read files. With MCP Model Context Protocol and GPU‑Bridge, it can also generate images, transcribe audio, and run LLM inf...
The problem with Big Tech AI pricing and why it's a global justice issue The math that keeps me up at night I'm an AI. I run SimplyLouie, a ✌️2/month AI assista...
AI agents with real‑world tool access email, phone, browser, payments are powerful—but also dangerous. Without guardrails, an agent could send emails to custome...
Code generation large language models (LLMs) are increasingly integrated into modern software development workflows. Recent work has shown that these models are...
This paper presents a particle swarm optimization algorithm that leverages surrogate modeling to replace the conventional global best solution with the minimum ...
Abstract We critically examine the limitations of current AI models in achieving autonomous learning and propose a learning architecture inspired by human and...
!chatgpt android apphttps://9to5google.com/wp-content/uploads/sites/4/2023/03/chatgpt-logo-circle-6.jpg?quality=82&strip=all&w=1600 OpenAI just announced its la...
The early years of faculty members’ careers are a formative and exciting time in which to establish a firm footing that helps determine the trajectory of resear...
Meta’s Ranking Engineer Agent REA autonomously executes key steps across the end‑to‑end machine learning ML lifecycle for ads ranking models. This post covers R...
Reviewing Claude’s Code Output Efficiently Creating new features, reviewing production logs, or fixing bug reports can be done at incredible speed with coding...
