From CycleGAN to DDPM: Advanced Techniques in Medical Ultrasound Image Synthesis

Table of Links Abstract and 1. Introduction II. Related Work III. Methodology IV. Experiments and Results V. Conclusion and References II. RELATED WORK A. Image-to-image translation Image-to-image translation is a domain of computer vision that focuses on transforming an image from one style or modality to another while preserving its underlying structure. This process is … Read more

Overcoming Data Scarcity: Semantic-Enhanced CycleGAN for Medical Ultrasound Synthesis

Table of Links Abstract and 1. Introduction II. Related Work III. Methodology IV. Experiments and Results V. Conclusion and References Abstract— Ultrasound imaging is pivotal in various medical diagnoses due to its non-invasive nature and safety. In clinical practice, the accuracy and precision of ultrasound image analysis are critical. Recent advancements in deep learning are … Read more

Future of AD Security: Addressing Limitations and Ethical Concerns in Typographic Attack Research

Table of Links Abstract and 1. Introduction Related Work 2.1 Vision-LLMs 2.2 Transferable Adversarial Attacks Preliminaries 3.1 Revisiting Auto-Regressive Vision-LLMs 3.2 Typographic Attacks in Vision-LLMs-based AD Systems Methodology 4.1 Auto-Generation of Typographic Attack 4.2 Augmentations of Typographic Attack 4.3 Realizations of Typographic Attacks Experiments Conclusion and References 6 Conclusion Our research has developed a comprehensive … Read more

Empirical Study: Evaluating Typographic Attack Effectiveness Against Vision-LLMs in AD Systems

Table of Links Abstract and 1. Introduction Related Work 2.1 Vision-LLMs 2.2 Transferable Adversarial Attacks Preliminaries 3.1 Revisiting Auto-Regressive Vision-LLMs 3.2 Typographic Attacks in Vision-LLMs-based AD Systems Methodology 4.1 Auto-Generation of Typographic Attack 4.2 Augmentations of Typographic Attack 4.3 Realizations of Typographic Attacks Experiments Conclusion and References 5 Experiments 5.1 Experimental Setup We perform experiments … Read more

Foreground vs. Background: Analyzing Typographic Attack Placement in Autonomous Driving Systems

Table of Links Abstract and 1. Introduction Related Work 2.1 Vision-LLMs 2.2 Transferable Adversarial Attacks Preliminaries 3.1 Revisiting Auto-Regressive Vision-LLMs 3.2 Typographic Attacks in Vision-LLMs-based AD Systems Methodology 4.1 Auto-Generation of Typographic Attack 4.2 Augmentations of Typographic Attack 4.3 Realizations of Typographic Attacks Experiments Conclusion and References 4.3 Realizations of Typographic Attacks Digitally, typographic attacks … Read more

The Role of Consistency and Sharing in Efficient Fine-Tuning

Table of Links Abstract and 1. Introduction Background 2.1 Mixture-of-Experts 2.2 Adapters Mixture-of-Adaptations 3.1 Routing Policy 3.2 Consistency regularization 3.3 Adaptation module merging and 3.4 Adaptation module sharing 3.5 Connection to Bayesian Neural Networks and Model Ensembling Experiments 4.1 Experimental Setup 4.2 Key Results 4.3 Ablation Study Related Work Conclusions Limitations Acknowledgment and References Appendix … Read more

End-to-End Deep Learning Improves CT Material Decomposition

Table of Links Abstract and 1 Introduction Dual-Energy CT Forward Model [Model-based Optimization Problem]() End-to-End Model-based Deep Learning for Material Decomposition (E2E-Decomp) Numerical Results Conclusion Compliance with Ethical Standards and References 4 End-to-End Model-based Deep Learning for Material Decomposition (E2E-Decomp) The workflow of the E2E-DEcomp algorithm at inference is shown in Fig. 1, and the … Read more

Klink Finance Disrupts Failing Web2 Ads – Launching $KLINK Token This October

London, UK – 1st October – As traditional Web2 advertising models face unprecedented challenges from privacy changes, cookie deprecation, and rising user acquisition costs, Klink Finance emerges as the infrastructure solution for the post-Web2 advertising era. The company announced the October launch of its $KLINK utility token, backed by proven revenue streams and a global … Read more

Smarter Fine-Tuning for NLU and NLG Tasks

Table of Links Abstract and 1. Introduction Background 2.1 Mixture-of-Experts 2.2 Adapters Mixture-of-Adaptations 3.1 Routing Policy 3.2 Consistency regularization 3.3 Adaptation module merging and 3.4 Adaptation module sharing 3.5 Connection to Bayesian Neural Networks and Model Ensembling Experiments 4.1 Experimental Setup 4.2 Key Results 4.3 Ablation Study Related Work Conclusions Limitations Acknowledgment and References Appendix … Read more

WEEX Powers TOKEN2049 Singapore as Platinum Sponsor Amidst Rapid CEX Growth

TOKEN2049 Singapore, the most influential crypto event in Asia, will take place on October 1–2, 2025 at Marina Bay Sands. This year, WEEX joins as a Platinum Sponsor, underscoring its commitment to the global digital asset community. The event will bring together thousands of leaders, investors, and innovators from around the world, and WEEX’s participation … Read more

How Mixture-of-Adaptations Makes Language Model Fine-Tuning Cheaper and Smarter

Table of Links Abstract and 1. Introduction Background 2.1 Mixture-of-Experts 2.2 Adapters Mixture-of-Adaptations 3.1 Routing Policy 3.2 Consistency regularization 3.3 Adaptation module merging and 3.4 Adaptation module sharing 3.5 Connection to Bayesian Neural Networks and Model Ensembling Experiments 4.1 Experimental Setup 4.2 Key Results 4.3 Ablation Study Related Work Conclusions Limitations Acknowledgment and References Appendix … Read more

How to Improve AI Models While Training Only 0.1% of Parameters

:::info Authors: (1) Yaqing Wang, Purdue University (wang5075@purdue.edu); (2) Sahaj Agarwal, Microsoft (sahagar@microsoft.com); (3) Subhabrata Mukherjee, Microsoft Research (submukhe@microsoft.com); (4) Xiaodong Liu, Microsoft Research (xiaodl@microsoft.com); (5) Jing Gao, Purdue University (jinggao@purdue.edu); (6) Ahmed Hassan Awadallah, Microsoft Research (hassanam@microsoft.com); (7) Jianfeng Gao, Microsoft Research (jfgao@microsoft.com). ::: Table of Links Abstract and 1. Introduction Background 2.1 Mixture-of-Experts … Read more

Moxie Marlinspike: The Cypherpunk Pirate Who Built Signal

Did you know that your daily messages on chats like WhatsApp and Facebook Messenger are encrypted thanks to this man? Considered a late cypherpunk and anarchist, Matthew Rosenfeld (better known as Moxie Marlinspike) is a remarkable American cryptographer and creator of privacy-focused digital tools for everyone. Marlinspike was born in the early eighties, grew up … Read more

The Battle for Agent Commerce: Google’s AP2 vs OpenAI’s ACP

We’re watching something pretty wild unfold right now. AI agents aren’t just chatting anymore, they’re starting to spend money. Your AI assistant might soon book your flight, renew your subscriptions, or order your groceries. Which, honestly, sounds convenient until you stop and think: wait, who’s making sure this thing doesn’t go rogue with my credit … Read more

Why a Decentralized Internet Might Still Silence Us

The internet began as a distributed network designed to resist single points of failure and maintain communication even under attack. The Advanced Research Projects Agency Network (ARPANET) embodied principles of decentralization and fault tolerance that seemed to promise genuine freedom of expression. Each node operated independently without reliance on central authorities. However, the commercialization of … Read more

The Metaphysics of the Event Horizon

Yes, I’m using an example of the sci-fi movie Event Horizon, a 1997 science fiction film directed by Paul Anderson and written by Philip Eisner. There are moments when science fiction doesn’t merely imagine the future – “It haunts it. “ In the 1997 cult-classic film Event Horizon, a spacecraft disappears during a test of … Read more

How I Trained A Small Language Model From Scratch

With the artificial intelligence ecosystem rapidly growing with different systems being built, it has reached its inflection point. While billions are being poured into ever larger models, these expenses do not reflect the ROI with 42% of these projects delivering zero ROI, and 88% of proof of concept not getting to production. The issue isn’t … Read more