Hi! I’ve tried to implement PPO for Mujoco based only on the paper and resources available at the time of publication, without looking at any existing implementations of the algorithm. I have now compared my implementation to the relevant details listed in The 37 Implementation Details of Proximal Policy Optimization, and it turns out I missed most details, see below. My question is: Were these details documented somewhere, or have they been known implicitly in the community at […]

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arXiv:2602.20300v1 Announce Type: new Abstract: Large Language Model (LLM) hallucinations are usually treated as defects of the model or its decoding strategy. Drawing on classical linguistics, we argue that a query’s form can also shape a listener’s (and model’s) response. We operationalize this insight by constructing a 22-dimension query feature vector covering clause complexity, lexical rarity, and anaphora, negation, answerability, and intention grounding, all known to affect human comprehension. Using 369,837 real-world queries, we ask: Are there certain […]

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Machine learning is a powerful method of extracting meaning from data; unfortunately, current digital hardware is extremely energy-intensive. There is interest in an alternative analog computing implementation that could match the performance of traditional machine learning while being significantly more energy-efficient. However, it remains unclear how to train such analog computing systems while adhering to locality constraints imposed by the physical (as opposed to digital) nature of these systems. Local learning algorithms such as Equilibrium Propagation and Coupled […]

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arXiv:2602.00998v1 Announce Type: new Abstract: Recent large language models (LLMs) perform strongly on mathematical benchmarks yet often misapply lemmas, importing conclusions without validating assumptions. We formalize lemma$-$judging as a structured prediction task: given a statement and a candidate lemma, the model must output a precondition check and a conclusion$-$utility check, from which a usefulness decision is derived. We present RULES, which encodes this specification via a two$-$section output and trains with reinforcement learning plus section$-$aware loss masking to […]

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We propose DeePM (Deep Portfolio Manager), a structured deep-learning macro portfolio manager trained end-to-end to maximize a robust, risk-adjusted utility. DeePM addresses three fundamental challenges in financial learning: (1) it resolves the asynchronous "ragged filtration" problem via a Directed Delay (Causal Sieve) mechanism that prioritizes causal impulse-response learning over information freshness; (2) it combats low signal-to-noise ratios via a Macroeconomic Graph Prior, regularizing cross-asset dependence according to economic first principles; and (3) it optimizes a distributionally robust objective […]

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Optimism, obsession, self-belief, raw horsepower and personal connections are how things get started. Cohesive teams, the right combination of calmness and urgency, and unreasonable commitment are how things get finished. Long-term orientation is in short supply; try not to worry about what people think in the short term, which will get easier over time. It is easier for a team to do a hard thing that really matters than to do an easy thing that doesn’t really matter; […]

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arXiv:2601.09900v1 Announce Type: new Abstract: This paper proposes specular differentiation in one-dimensional Euclidean space and provides its fundamental analysis, including quasi-Fermat’s theorem and the quasi-Mean Value Theorem. As an application, this paper develops several numerical schemes for solving initial value problems for first-order ordinary differential equations. Based on numerical simulations, we select one scheme and prove its first-order consistency and second-order local convergence.

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How are you, hacker? 🪐 What’s happening in tech today, January 3, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Alaska became the 49th US state in 1959, The first block of the Bitcoin blockchain was mined in 2009, Panama leader Manuel Noriega surrendered to US authorities in 1990, and we present you with these top quality stories. From 10 Noteworthy C and C++ Bugs Found in Open-Source Projects in 2025 […]

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arXiv:2602.16736v1 Announce Type: new Abstract: This paper presents empirical results from a production-grade C++ implementation of a deterministic semantic state substrate derived from prior formal work on Bounded Local Generator Classes (Martin, 2026). The system was mathematically specified prior to implementation and realized as a CPU-resident graph engine operating under bounded local state evolution. Contemporary inference-driven AI architectures reconstruct semantic state through probabilistic recomposition, producing compute cost that scales with token volume and context horizon. In contrast, the […]

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