arXiv:2601.05374v1 Announce Type: cross Abstract: Empirical models of demand for differentiated products rely on low-dimensional product representations to capture substitution patterns. These representations are increasingly proxied by applying ML methods to high-dimensional, unstructured data, including product descriptions and images. When proxies fail to capture the true dimensions of differentiation that drive substitution, standard workflows will deliver biased counterfactuals and invalid inference. We develop a practical toolkit that corrects this bias and ensures valid inference for a broad class […]

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Key Highlights: Europe is one of the markets across the globe where tech giants find themselves under heavy scrutiny from the European Commission. Meta, this time, has found itself in a spot of bother after introducing a WhatsApp policy that blocks third-party AI providers.  Italy’s antitrust regulator asks Meta to suspend its WhatsApp policy that blocks third-party AI providers Earlier this month, the European Commission launched a separate investigation into this matter. At the time, the regulator announced […]

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A composite loss assigns a penalty to a real-valued prediction by associating the prediction with a probability via a link function then applying a class probability estimation (CPE) loss. If the risk for a composite loss is always minimised by predicting the value associated with the true class probability the composite loss is proper. We provide a novel, explicit and complete characterisation of the convexity of any proper composite loss in terms of its link and its “weight […]

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Processing images to generate text, such as image captioning and visual question-answering, has been studied for years. Traditionally such systems rely on an object detection network as a vision encoder to capture visual features and then produce text via a text decoder. Given a large amount of existing literature, in this post, I would like to only focus on one approach for solving vision language tasks, which is to extend pre-trained generalized language models to be capable of […]

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Stochastic gradient descent is a universal choice for optimizing deep learning models. However, it is not the only option. With black-box optimization algorithms, you can evaluate a target function $f(x): mathbb{R}^n to mathbb{R}$, even when you don’t know the precise analytic form of $f(x)$ and thus cannot compute gradients or the Hessian matrix. Examples of black-box optimization methods include Simulated Annealing, Hill Climbing and Nelder-Mead method.

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Group-based reinforcement learning methods, like Group Relative Policy Optimization (GRPO), are widely used nowadays to post-train large language models. Despite their empirical success, they exhibit structural mismatches between reward optimization and the underlying training objective. In this paper, we present a theoretical analysis of GRPO style methods by studying them within a unified surrogate formulation. This perspective reveals recurring properties that affect all the methods under analysis: (i) non-uniform group weighting induces systematic gradient biases on shared prefix […]

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Technology is supercharging the attack on democracy by making it easier to spy on people, block free speech, and control what we do. The Electronic Frontier Foundation’s activists, lawyers, and technologists are fighting back. Join the movement to Take Back CTRL. DONATE TODAY Join EFF and Fight Back Take Back CTRL is EFF’s new website to give you insight into the ways that technology has become the veins and arteries of rising global authoritarianism. It’s not just because […]

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arXiv:2601.04349v1 Announce Type: new Abstract: Scientific research increasingly depends on robust and scalable IT infrastructures to support complex computational workflows. With the proliferation of services provided by research infrastructures, NRENs, and commercial cloud providers, researchers must navigate a fragmented ecosystem of computing environments, balancing performance, cost, scalability, and accessibility. Hybrid cloud architectures offer a compelling solution by integrating multiple computing environments to enhance flexibility, resource efficiency, and access to specialised hardware. This paper provides a comprehensive overview of […]

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