Author(s): Abhishek Yadav Originally published on Towards AI. A hands-on guide to building synthetic data that looks, feels, and behaves like the real world without privacy risk Photo by Luke Chesser on Unsplash Healthcare organizations sit on treasure chests of data be it the appointments, lab results, care journeys, billing patterns, social determinants. Yet the very rules designed to protect patient privacy often make it nearly impossible for analysts and data scientists to experiment freely. And that’s a […]

Ver mais

arXiv:2602.03879v1 Announce Type: new Abstract: To address the trade-off between computational efficiency and adherence to Kolmogorov-Arnold Network (KAN) principles, we propose TruKAN, a new architecture based on the KAN structure and learnable activation functions. TruKAN replaces the B-spline basis in KAN with a family of truncated power functions derived from k-order spline theory. This change maintains the KAN’s expressiveness while enhancing accuracy and training time. Each TruKAN layer combines a truncated power term with a polynomial term and […]

Ver mais

arXiv:2601.15339v1 Announce Type: new Abstract: Code understanding is a foundational capability in software engineering tools and developer workflows. However, most existing systems are designed for English-speaking users interacting via keyboards, which limits accessibility in multilingual and voice-first settings, particularly in regions like India. Voice-based interfaces offer a more inclusive modality, but spoken queries involving code present unique challenges due to the presence of non-standard English usage, domain-specific vocabulary, and custom identifiers such as variable and function names, often […]

Ver mais

I am working on applying AI/ML to seismic interpretation for oil exploration The problems are classic pattern recognition but with hard constraints: • Very low signal to noise ratio • Sparse and uncertain labels • Features that are visually interpretable to geoscientists but difficult to formalize (continuity, terminations, subtle amplitude changes) Typical use cases include reservoir body detection (channels, lobes) and separating geological signal from acquisition or processing artifacts. For people who have worked on scientific or medical […]

Ver mais

arXiv:2512.21577v2 Announce Type: replace-cross Abstract: Despite numerous attempts at mitigation since the inception of language models, hallucinations remain a persistent problem even in today’s frontier LLMs. Why is this? We review existing definitions of hallucination and fold them into a single, unified definition wherein prior definitions are subsumed. We argue that hallucination can be unified by defining it as simply inaccurate (internal) world modeling, in a form where it is observable to the user. For example, stating a […]

Ver mais

We develop a new form of reweighting (Wainwright et al., 2005b) to leverage the relationship between Ising spin glasses and perfect matchings into a novel technique for the exact computation of MAP states in hitherto intractable binary Markov random fields. Our method solves an $n times n$ lattice with external field and random couplings much faster, and for larger $n$, than the best competing algorithms. It empirically scales as $O(n^3)$ even though this problem is NP-hard and non-approximable […]

Ver mais

The Marvel Cinematic Universe (MCU) has been ongoing since 2008. Dozens of tv shows and movies later, so many incredible characters have been introduced to the general public. Characters that were only known to comic book fans became worldwide icons. If you go anywhere in the world and say, “I am Groot,” there’s a good chance that somebody will get your reference. But even still, there are a ton of characters that have remained surprisingly unused. Here are […]

Ver mais

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 […]

Ver mais

Data science agents should inspect datasets, design workflows, run code, and return verifiable answers, not just autocomplete Pandas code. DSGym, introduced by researchers from Stanford University, Together AI, Duke University, and Harvard University, is a framework that evaluates and trains such agents across more than 1,000 data science challenges with expert curated ground truth and a consistent post training pipeline. https://arxiv.org/pdf/2601.16344 Why existing benchmarks fall short? The research team first probe existing benchmarks that claim to test data […]

Ver mais