arXiv:2601.08040v1 Announce Type: new Abstract: Scientific image manipulation in biomedical publications poses a growing threat to research integrity and reproducibility. Unlike natural image forensics, biomedical forgery detection is uniquely challenging due to domain-specific artifacts, complex textures, and unstructured figure layouts. We present the first vision-language guided framework for both generating and detecting biomedical image forgeries. By combining diffusion-based synthesis with vision-language prompting, our method enables realistic and semantically controlled manipulations, including duplication, splicing, and region removal, across diverse […]

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arXiv:2603.06599v1 Announce Type: new Abstract: Artificial intelligence pipelines — spanning data collection, model training, deployment, and post-deployment monitoring — concentrate ethical risks that intensify with multimodal and agentic systems. Existing governance instruments, including the EU AI Act, the IEEE 7000 series, and the NIST AI Risk Management Framework, provide high-level guidance but often lack enforceable, end-to-end operational controls. This paper presents an ethics-by-design control architecture that embeds consequentialist, deontological, and virtue-ethical reasoning into stage-specific enforcement mechanisms across the […]

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Superhuman AI Exfiltrates Emails Classic prompt injection attack: When asked to summarize the user’s recent mail, a prompt injection in an untrusted email manipulated Superhuman AI to submit content from dozens of other sensitive emails (including financial, legal, and medical information) in the user’s inbox to an attacker’s Google Form. To Superhuman’s credit they treated this as the high priority incident it is and issued a fix. The root cause was a CSP rule that allowed markdown images […]

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Molecular representations are inherently task-dependent, yet most pre-trained molecular encoders are not. Task conditioning promises representations that reorganize based on task descriptions, but existing approaches rely on expensive labeled data. We show that weak supervision on programmatically derived molecular motifs is sufficient. Our Adaptive Chemical Embedding Model (ACE-Mol) learns from hundreds of motifs paired with natural language descriptors that are cheap to compute, trivial to scale. Conventional encoders slowly search the embedding space for task-relevant structure, whereas ACE-Mol […]

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Leading your organization to use OpenTelemetry is a challenge. In addition to all the usual project hurdles, you’ll face one of these two situations: convince your teams to use OpenTelemetry, or convince them to move from the telemetry tool they are already using to OpenTelemetry. Most people don’t want to change. You’ll need lots of effort and baby steps. My tip is the following: the fewer the changes, the higher your chances of success. In this post, I […]

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arXiv:2602.18571v1 Announce Type: new Abstract: While significant progress has been made in automating various aspects of software development through coding agents, there is still significant room for improvement in their bug fixing capabilities. Debugging and investigation of runtime behavior remains largely a manual, developer-driven process. Popular coding agents typically rely on either static analysis of the code or iterative test-fix cycles, which is akin to trial and error debugging. We posit that there is a wealth of rich […]

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arXiv:2603.06668v1 Announce Type: new Abstract: The stability of Internet services is persistently challenged by the escalating scale of volumetric TCP SYN floods, as conventional defenses like SYN Cookies fail by exacerbating bandwidth depletion under modern attacks. This paper introduces SDN-SYN PoW, a novel defense architecture that synergizes non-interactive Proof-of-Work with a Software-Defined Networking (SDN) control plane, an approach particularly effective for securing the network edge in modern SD-WAN deployments. The core innovation is its ability to perform global […]

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arXiv:2601.16298v1 Announce Type: new Abstract: With the rise of decentralized finance, fiat-to-cryptocurrency exchange platforms have become popular entry points into the cryptocurrency ecosystem. However, these platforms frequently fail to ensure adequate privacy protection, as evidenced by real-world breaches that exposed personally identifiable information (PII) and crypto addresses. Such leaks enable adversaries to link real-world identities to cryptocurrency transactions, undermining the presumed anonymity of cryptocurrency use. We propose FC-GUARD, a privacy-preserving exchange system designed to preserve user anonymity without […]

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arXiv:2602.10252v1 Announce Type: new Abstract: Datacenter networks are currently locked in a “tyranny of the single objective”. While modern workloads demand diverse performance goals, ranging from coflow completion times, per-flow fairness, short-flow latencies, existing fabrics are typically hardcoded for a single metric. This rigid coupling ensures peak performance when application and network objectives align, but results in abysmal performance when they diverge. We propose DMart, a decentralized scheduling framework that treats network bandwidth as a competitive marketplace. In […]

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