Continual learning is a challenge for models with static architecture, as they fail to adapt to when data distributions evolve across tasks. We introduce a mathematical framework that jointly models architecture and weights in a Sobolev space, enabling a rigorous investigation into the role of neural network architecture in continual learning and its effect on the forgetting loss. We derive necessary conditions for the continual learning solution and prove that learning only model weights is insufficient to mitigate […]

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We propose a generalization of the Multiple-try Metropolis (MTM) algorithm of Liu et al. (2000), which is based on drawing several proposals at each step and randomly choosing one of them on the basis of weights that may be arbitrary chosen. In particular, for Bayesian estimation we also introduce a method based on weights depending on a quadratic approximation of the posterior distribution. The resulting algorithm cannot be reformulated as an MTM algorithm and leads to a comparable […]

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Our treasured language lets us leverage powerful tools and guard us from countless implementation details. Although exceptions have a bad name among many developers, a detailed analysis of how they work can greatly expand your understanding of how C++ really works. That’s what we’ll do! Before diving into the depths of exceptions let pick a right angle to how they could possibly work. In general, there are two options: the landing pad or via the frame handler. Sorry, […]

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Characterising Bias in Compressed Models by Sara Hooker et al highlighted where the lunch was getting paid when it came to modern deep learning compression techniques. All of these models we use on a pervasive basis, in her phones, on social feeds, etc, they all use compression. Are we compromising what we want when we apply this everywhere? More particularly, are we affecting some groups more than others?

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In this edition of our Haskell in Production series, we interview developers from Verity – a company that provides integrated solutions for modern asset management. Questions in this article were answered jointly by Dima Rogozin, VP of Engineering at Verity, and Arsani Gaied and Tim McIver who are senior Haskell developers at the company. Read further to learn why they use Haskell and what has been their experience so far. Interview with Verity Could you give our readers […]

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arXiv:2601.16378v1 Announce Type: new Abstract: Multimodal language models (MLMs) perform well on semantic vision-language tasks but fail at spatial reasoning that requires adopting another agent’s visual perspective. These errors reflect a persistent egocentric bias and raise questions about whether current models support allocentric reasoning. Inspired by human spatial cognition, we introduce perspective tokens, specialized embeddings that encode orientation through either (1) embodied body-keypoint cues or (2) abstract representations supporting mental rotation. Integrating these tokens into LLaVA-1.5-13B yields performance […]

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Teilhard casts scientific research as humanity’s next evolutionary pulse—our collective mind awakening to shape its own future. He argues that the modern hunger to know and create is nothing less than evolution reflecting on itself, a divine power working through human inquiry. For him, research becomes sacred: the meeting point where faith in God and faith in human potential fuse into a single, world-transforming spiritual force.

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