Word Embeddings in NLP: From Bag-of-Words to Transformers (Part 1)

Word Embeddings in NLP: From Bag-of-Words to Transformers (Part 1)

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Image generated with Microsoft Copilot · 1. Introduction: Why Computers Struggle with Language· 2. What Are Word Embeddings and Why Do We Need Them? ∘ The Map Analogy ∘ Why We Need Them ∘ Word embeddings fix this by encoding meaning: ∘ The Core Idea ∘ Why This Revolutionized NLP· 3. Types of Word Embeddings: From Simple to Sophisticated ∘ The Three Generations ∘ Why This Progression Matters· 3.1 Frequency-Based Embeddings (The Starting Point) ∘ 3.1.1. Bag-of-Words (BoW) […]

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EPA makes it harder for states, tribes to block pipelines

EPA makes it harder for states, tribes to block pipelines

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The Trump administration on Tuesday proposed a new rule aimed at speeding up and streamlining the permitting process for large energy and infrastructure projects, including oil and gas pipelines and facilities tied to artificial intelligence. The rule, which does not require action by Congress, includes a suite of procedural changes to section 401 of the Clean Water Act—a law enacted in the 1970s that is the primary federal statute governing water pollution in the United States. For decades, […]

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Local Recovery of Magnetic Invariants from Local Length Measurements in Non-Reversible Randers Metrics

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We study a purely local inverse problem for non-reversible Randers metrics ( F = |cdot|_g + beta ) defined on smooth oriented surfaces. Using only the lengths of sufficiently small closed curves around a point ( p ), we prove that the exterior derivative ( dbeta(p) ) can be uniquely and stably recovered. Moreover, we establish that ( dbeta(p) ) is the only second-order local invariant retrievable from such local length measurements. Our approach is entirely metric-based, independent […]

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New undersea cable cutter risks Internet’s backbone

New undersea cable cutter risks Internet’s backbone

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A Chinese ship has tested a new device capable of slicing through submarine data cables thousands of meters beneath the ocean surface. That demonstration may exacerbate security concerns over a spate of suspected sabotage incidents targeting undersea communications and power cables from the Baltic Sea to the Pacific Ocean. The trial took place at a depth of 11,483 feet (3,500 meters) during a deep-sea science expedition involving the Chinese research ship named Haiyang Dizhi 2, according to the […]

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ClawWorm: Self-Propagating Attacks Across LLM Agent Ecosystems

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arXiv:2603.15727v1 Announce Type: new Abstract: Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multi-agent ecosystems, whose security properties remain largely unexplored. In particular, OpenClaw, an open-source platform with over 40{,}000 active instances, has stood out recently with its persistent configurations, tool-execution privileges, and cross-platform messaging capabilities. In this work, we present ClawWorm, the first self-replicating worm attack against a production-scale agent framework, achieving a fully autonomous infection cycle initiated by a single message: the worm […]

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NASA's Moon ship and rocket seem to be working well, so what about the landers?

NASA’s Moon ship and rocket seem to be working well, so what about the landers?

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As we have been reporting on Ars, NASA’s Artemis II lunar mission has been going rather well so far. Of course, Orion’s big test is yet to come with the fiery reentry through Earth’s atmosphere on Friday. But so far, it’s looking like the rocket and spaceship needed for a lunar landing are getting there for NASA. The biggest remaining piece of the architecture, therefore, is a lunar lander. Known in NASA parlance as the Human Landing System, […]

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GDEV-AI: A Generalized Evaluation of Deep Learning Inference Scaling and Architectural Saturation

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arXiv:2602.16858v1 Announce Type: new Abstract: The deployment of deep learning inference in production environments continues to grow, where throughput, latency, and hardware efficiency are critical. Although specialized accelerators are increasingly adopted, many inference workloads still run on CPU-only systems, particularly in legacy data centers and cost-sensitive environments. This study investigates the scalability limits of CPU-based inference for convolutional neural networks by benchmarking ResNet models across varying batch sizes on two hardware tiers: a legacy Intel Xeon E5-2403 v2 […]

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Robust Self-Training with Closed-loop Label Correction for Learning from Noisy Labels

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Training deep neural networks with noisy labels remains a significant challenge, often leading to degraded performance. Existing methods for handling label noise typically rely on either transition matrix, noise detection, or meta-learning techniques, but they often exhibit low utilization efficiency of noisy samples and incur high computational costs. In this paper, we propose a self-training label correction framework using decoupled bilevel optimization, where a classifier and neural correction function co-evolve. Leveraging a small clean dataset, our method employs […]

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Weekly Review: 10/21/2017

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Its been a long while since I last posted, but for good reason! I was busy shifting base from Google’s Hyderabad office to their new location in Sunnyvale. This is my first time in the USA, so there is a lot to take in and process! Anyway, I am now working on Google’s Social-Search and Ranking team. At the same time, I am also doing Coursera’s Robotics Specialization to learn a subject I have never really touched upon. […]

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Statistical-Geometric Degeneracy in UAV Search: A Physics-Aware Asymmetric Filtering Approach

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arXiv:2602.15893v1 Announce Type: new Abstract: Post-disaster survivor localization using Unmanned Aerial Vehicles (UAVs) faces a fundamental physical challenge: the prevalence of Non-Line-of-Sight (NLOS) propagation in collapsed structures. Unlike standard Gaussian noise, signal reflection from debris introduces strictly non-negative ranging biases. Existing robust estimators, typically designed with symmetric loss functions (e.g., Huber or Tukey), implicitly rely on the assumption of error symmetry. Consequently, they experience a theoretical mismatch in this regime, leading to a phenomenon we formally identify as […]

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