arXiv:2601.08867v1 Announce Type: new Abstract: Recently, reconstruction-based methods have gained attention for AIGC image detection. These methods leverage pre-trained diffusion models to reconstruct inputs and measure residuals for distinguishing real from fake images. Their key advantage lies in reducing reliance on dataset-specific artifacts and improving generalization under distribution shifts. However, they are limited by significant inefficiency due to multi-step inversion and reconstruction, and their reliance on diffusion backbones further limits generalization to other generative paradigms such as GANs. […]

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arXiv:2602.17856v1 Announce Type: new Abstract: This paper investigates the enhancement of scientific literature chatbots through retrieval-augmented generation (RAG), with a focus on evaluating vector- and graph-based retrieval systems. The proposed chatbot leverages both structured (graph) and unstructured (vector) databases to access scientific articles and gray literature, enabling efficient triage of sources according to research objectives. To systematically assess performance, we examine two use-case scenarios: retrieval from a single uploaded document and retrieval from a large-scale corpus. Benchmark test […]

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Nonequilibrium electronic forces play a central role in voltage-driven phase transitions but are notoriously expensive to evaluate in dynamical simulations. Here we develop a machine learning framework for adiabatic lattice dynamics coupled to nonequilibrium electrons, and demonstrate it for a gating induced insulator to metal transition out of a charge density wave state in the Holstein model. Although exact electronic forces can be obtained from nonequilibrium Green’s function (NEGF) calculations, their high computational cost renders long time dynamical […]

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arXiv:2601.05466v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse applications, however, they remain critically vulnerable to jailbreak attacks that elicit harmful responses violating human values and safety guidelines. Despite extensive research on defense mechanisms, existing safeguards prove insufficient against sophisticated adversarial strategies. In this work, we propose iMIST (underline{i}nteractive underline{M}ulti-step underline{P}rogreunderline{s}sive underline{T}ool-disguised Jailbreak Attack), a novel adaptive jailbreak method that synergistically exploits vulnerabilities in current defense mechanisms. iMIST disguises malicious queries as […]

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I am a figurative artist based in New York with work in the collections of the Metropolitan Museum of Art, MoMA, SFMOMA, and the British Museum. I recently published my catalog raisonne as an open dataset on Hugging Face. Dataset overview: 3,000 to 4,000 images currently, with approximately double that to be added as scanning continues Single artist, single primary subject: the human figure across five decades Media spans oil on canvas, works on paper, drawings, etchings, lithographs, […]

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Federated learning (FL) suffers from performance degradation due to the inevitable presence of noisy annotations in distributed scenarios. Existing approaches have advanced in distinguishing noisy samples from the dataset for label correction by leveraging loss values. However, noisy samples recognition relying on scalar loss lacks reliability for FL under heterogeneous scenarios. In this paper, we rethink this paradigm from a representation perspective and propose method~(textbf{Fed}erated under textbf{R}epresentation textbf{G}emometry), which follows textbf{the principle of “representation geometry priority”} to recognize […]

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Previously, businesses have taken disruption lightly. Something to live with, something to respond to, something that will culminate. This closure of factories, collapse of suppliers, logistical difficulties, and system failures are all unwanted guests, and they push leaders to enter the crisis mode. The fag-end work is in teams, and decisions are fast; spending is too big, and hopefully it will be the environment, the next shock to be felt somewhere in the environment. Such a way of […]

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How I designed a single Python backend that serves a real estate agency in Dubai, a dental practice in Brazil, and a food retailer — each with fully isolated AI behavior, context memory, and business logic — without any off-the-shelf automation tools. Most WhatsApp AI tutorials show you how to build a bot for one use case. You connect to the API, craft a system prompt, call OpenAI, send a reply. It works. But it doesn’t scale. When I started building AI automation […]

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How Pattern Recognition Architecture Accidentally Became Behavioral Psychology at Scale The discourse surrounding artificial intelligence has long centered on computational capability — model parameters, benchmark scores, reasoning depth. Yet the most profound transformation in human-AI interaction stems not from architectural sophistication, but from an emergent capability that was never explicitly programmed: affective pattern recognition at the micro-behavioral level. What we’re witnessing isn’t the creation of artificial empathy. It’s something far more consequential: the systematic extraction and modeling of human emotional architecture […]

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