arXiv:2601.04233v1 Announce Type: new Abstract: We present the LEMAS-Dataset, which, to our knowledge, is currently the largest open-source multilingual speech corpus with word-level timestamps. Covering over 150,000 hours across 10 major languages, LEMAS-Dataset is constructed via a efficient data processing pipeline that ensures high-quality data and annotations. To validate the effectiveness of LEMAS-Dataset across diverse generative paradigms, we train two benchmark models with distinct architectures and task specializations on this dataset. LEMAS-TTS, built upon a non-autoregressive flow-matching framework, […]

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Are code and data available? Yes, code and data are on GitHub. Code includes both Monte Carlo conformal prediction as well as the plausibility regions from v1 of the paper. Can you derive the conformal $p$-values used in the paper? The connection of conformal prediction and $p$-values is scattered across the literature and there is, to the best of my knowledge, no good reference to understand this. So we added a thorough derivation in Appendix B of the […]

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In top crypto news today, investors are seeking the best crypto to buy now amid volatile markets. Solana (SOL) has long been viewed as a top crypto, but recent indicators reveal vulnerabilities that make it less appealing as the best crypto to buy now. Instead, attention shifts to Mutuum Finance (MUTM), an innovative DeFi crypto priced at $0.04, positioning itself as the next big crypto with strong fundamentals. Since its presale began, MUTM has raised $19,600,000 from 18,650 […]

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I mentioned bi-twin prime chains in the previous post, but didn’t say much about them so as not to interrupt the flow of the article. A pair of prime numbers are called twins if they differ by 2. For example, 17 and 19 are twin primes. A bi-twin chain is a sequence of twin primes in which the average of each twin pair is double that of the preceding pair. For example, 5, 7, 11, 13 is a […]

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Federated learning (FL) enables collaborative model training across distributed clients without sharing raw data, yet its stability is fundamentally challenged by statistical heterogeneity in realistic deployments. Here, we show that client heterogeneity destabilizes FL primarily by distorting local gradient dynamics during client-side optimization, causing systematic drift that accumulates across communication rounds and impedes global convergence. This observation highlights local gradients as a key regulatory lever for stabilizing heterogeneous FL systems. Building on this insight, we develop a general […]

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Prompt Chaining: When One Prompt Isn’t Enough If you’ve ever tried to squeeze an entire project into one prompt—requirements → solution → plan → risks → final doc—you already know how it ends: it skips steps, it forgets constraints, it gives you a “confident” answer you can’t easily verify, and the moment something is wrong, you have no idea where the mistake happened. Prompt Chaining is the fix. Think of it as building a workflow where each prompt […]

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GPT-5.2 is OpenAI’s strongest model yet for math and science, setting new state-of-the-art results on benchmarks like GPQA Diamond and FrontierMath. This post shows how those gains translate into real research progress, including solving an open theoretical problem and generating reliable mathematical proofs.

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Author(s): Hayanan Originally published on Towards AI. Unveiling the Magic of Gradient Descent, Feedforward Architectures, and Universal Function Approximation in AI Ne‌ural⁠ networks‌ form the backbone of mod‌ern artifici⁠al inte​lligence, powering b‍rea⁠kthroughs in computer v⁠ision, natur⁠al language pro‌cess‍ing,​ re‍commende‍r syst‌ems, and s⁠cientific disc​overy​.‍ Yet beneath today’s deep architectures lie simple mathematic⁠a‌l ideas developed deca‍de​s‌ ago. T‌his a‍rticle pr⁠esents a⁠ c‍omprehensive, e⁠nd-to-end jo​urney⁠ thro‌ugh the evolution of neur​al‍ net‍wo​rks fr‌om the foundational percep⁠tro‌n to sigmoid n​euro‌ns, g‌radient-based l‌earn‌ing, feedfo‍rwar⁠d​ […]

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