arXiv:2601.00003v1 Announce Type: new Abstract: Large language models (LLMs) typically enhance their performance through either the retrieval of semantically similar information or the improvement of their reasoning capabilities. However, a significant challenge remains in effectively integrating both retrieval and reasoning strategies to optimize LLM performance. In this paper, we introduce a reasoning-aware knowledge retrieval method that enriches LLMs with information aligned to the logical structure of conversations, moving beyond surface-level semantic similarity. We follow a coarse-to-fine approach for […]

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arXiv:2601.14289v1 Announce Type: new Abstract: Understanding research papers remains challenging for foundation models due to specialized scientific discourse and complex figures and tables, yet existing benchmarks offer limited fine-grained evaluation at scale. To address this gap, we introduce RPC-Bench, a large-scale question-answering benchmark built from review-rebuttal exchanges of high-quality computer science papers, containing 15K human-verified QA pairs. We design a fine-grained taxonomy aligned with the scientific research flow to assess models’ ability to understand and answer why, what, […]

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In quantitative trading, it’s important to be careful when testing your strategy on all available data, as this can sometimes cause the rules to become too tuned and not perform well in real trading situations. To get a better idea of how your strategy really works, try dividing your historical data into a training (or optimisation) period and a test period. This approach allows you to evaluate your strategy on unseen data, much like real market conditions, which […]

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arXiv:2601.04673v1 Announce Type: cross Abstract: Estimating causal effects from observational data remains a fundamental challenge in causal inference, especially in the presence of latent confounders. This paper focuses on estimating causal effects in Gaussian Linear Structural Causal Models (GL-SCMs), which are widely used due to their analytical tractability. However, parameter estimation in GL-SCMs is often infeasible with finite data, primarily due to overparameterization. To address this, we introduce the class of Centralized Gaussian Linear SCMs (CGL-SCMs), a simplified […]

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When people talk about premium domains, the conversation usually stops at price. A domain that costs $12 per year versus one that costs $1,200 up front feels like an obvious tradeoff. But the difference between premium and non-premium domains isn’t just branding or vanity. There are technical, economic, and product-level implications that matter more than most founders realize. This article breaks down what actually makes a domain “premium,” how that differs from standard registrations, and when paying extra […]

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The source, written by Esteban Remecz, a CIO VP at Maxion Wheels, explores the likely trends of Artificial Intelligence (AI) in 2024 and beyond. Remecz emphasizes the exponential growth of AI across various industries, predicting a possible singularity in 2026-2028. The author discusses the potential benefits of AI in fields like healthcare, education, and cybersecurity, while also addressing the ethical and legal challenges associated with its increasing influence. He highlights the importance of developing ethical frameworks and regulations […]

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Sequential Bayesian optimal experimental design (SBOED) for PDE-governed inverse problems is computationally challenging, especially for infinite-dimensional random field parameters. High-fidelity approaches require repeated forward and adjoint PDE solves inside nested Bayesian inversion and design loops. We formulate SBOED as a finite-horizon Markov decision process and learn an amortized design policy via policy-gradient reinforcement learning (PGRL), enabling online design selection from the experiment history without repeatedly solving an SBOED optimization problem. To make policy training and reward evaluation scalable, […]

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Modern education is dangerously fragmented: rich in expertise, poor in meaning. True understanding requires “bridge-builders” who unite science, art, ethics, and lived experience, forging a shared language that reconnects facts with values, knowledge with love, and intellect with the whole of human life.

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Hi all, I’m starting hitting the limit of my homelab GPU (RTX 5070 8GB or Mac Mini M4 with integrated GPU) with my distillation experiment and is not the right moment to spent thousand euros to get something better. Say that, is there same cloud service that give you the entire server with GPU (so not pod, vm or stranger things) that: – Have affordable price => let’s say 100-120eur per months will be nice, but I’m open […]

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arXiv:2512.20368v2 Announce Type: replace Abstract: Statistical inference in contextual bandits is challenging due to the adaptive, non-i.i.d. nature of the data. A growing body of work shows that classical least-squares inference can fail under adaptive sampling, and that valid confidence intervals for linear functionals typically require an inflation of order $sqrt{d log T}$. This phenomenon — often termed the price of adaptivity — reflects the intrinsic difficulty of reliable inference under general contextual bandit policies. A key structural […]

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