Key Takeaways Digital PR delivers compounding returns: a single feature in a respected publication can drive traffic, backlinks, and brand authority for years Privacy regulations and Apple’s ATT framework have eroded paid ad attribution, making it harder to prove what your spend actually generates AI-driven search results favour brands that already appear in trusted editorial sources, giving digital PR a direct line to long-term discoverability Editorial coverage in respected publications carries social proof that converts both customers and […]

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Retrieval-augmented generation (RAG) is increasingly deployed in real-world applications, where its reference-grounded design makes outputs appear trustworthy. This trust has spurred research on poisoning attacks that craft malicious content, inject it into knowledge sources, and manipulate RAG responses. However, when evaluated in practical RAG systems, existing attacks suffer from severely degraded effectiveness. This gap stems from two overlooked realities: (i) content is often processed before use, which can fragment the poison and weaken its effect, and (ii) users […]

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arXiv:2510.11546v2 Announce Type: replace Abstract: High-dimensional regression often suffers from heavy-tailed noise and outliers, which can severely undermine the reliability of least-squares based methods. To improve robustness, we adopt a non-smooth Wilcoxon score based rank objective and incorporate structured group sparsity regularization, a natural generalization of the lasso, yielding a group lasso regularized rank regression method. By extending the tuning-free parameter selection scheme originally developed for the lasso, we introduce a data-driven, simulation-based tuning rule and further establish […]

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arXiv:2602.03980v1 Announce Type: new Abstract: Because language is creative, any reasonable language model must generalize, deciding what to say in novel contexts by using information from similar contexts. But what about contexts that are not novel but merely infrequent? In hierarchical regression, the model’s predictions for behavior in a context are affected by observations from other similar contexts to the extent that 1) the current context is infrequent and 2) different contexts behave similarly. This is called adaptive […]

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arXiv:2601.14470v1 Announce Type: new Abstract: LLM-based Multi-Agent (LLM-MA) systems are increasingly applied to automate complex software engineering tasks such as requirements engineering, code generation, and testing. However, their operational efficiency and resource consumption remain poorly understood, hindering practical adoption due to unpredictable costs and environmental impact. To address this, we conduct an analysis of token consumption patterns in an LLM-MA system within the Software Development Life Cycle (SDLC), aiming to understand where tokens are consumed across distinct software […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The Long Now of the Web: Inside the Internet Archive’s Fight Against Forgetting By @zbruceli [ 18 Min read ] A deep dive into the Internet Archive’s custom tech stack. Read More. The SEPA Instant Deadlines Have Passed. But Did Europe Really Go Instant? […]

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A DevSecOps engineer’s honest account of building an AI agent grounded in real tenant data — including the parts that didn’t work. A note on scope: This is an experimental project built with a vision for future integration into a real business process. It is not yet production-grade. Enterprise AI agent platforms like Azure AI Foundry, AWS Bedrock Agents, and Google Vertex AI Agent Builder offer managed infrastructure, safety controls, and scalability that this implementation doesn’t. This is a learning exercise — with […]

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Cloud cost and system reliability are the same problem viewed through different instruments. Cost anomalies surface bugs, retry storms, and memory leaks before they cause outages — if you’re watching. The fix: embed billing telemetry into your observability stack, enforce resource tagging at the pipeline level, write anomaly-based cost alerts, and treat budget overruns as budget burns the same way you treat SLO violations. Manage them separately and you’ll always be six weeks behind the failure that caused […]

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arXiv:2601.08843v1 Announce Type: new Abstract: Automated short-answer grading (ASAG) remains a challenging task due to the linguistic variability of student responses and the need for nuanced, rubric-aligned partial credit. While Large Language Models (LLMs) offer a promising solution, their reliability as automated judges in rubric-based settings requires rigorous assessment. In this paper, we systematically evaluate the performance of LLM-judges for rubric-based short-answer grading. We investigate three key aspects: the alignment of LLM grading with expert judgment across varying […]

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