March 2026

We compare liquid neural networks with mixture density heads against diffusion policies on Push-T, RoboMimic Can, and PointMaze under a shared-backbone comparison protocol that isolates policy-head effects under matched inputs, training budgets, and evaluation settings. Across tasks, liquid policies use roughly half the parameters (4.3M vs. 8.6M), achieve 2.4x lower offline prediction error, and run 1.8 faster at inference. In sample-efficiency experiments spanning 1% to 46.42% of training data, liquid models remain consistently more robust, with especially large […]

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In this tutorial, we implement IWE: an open-source, Rust-powered personal knowledge management system that treats markdown notes as a navigable knowledge graph. Since IWE is a CLI/LSP tool designed for local editors. We build a realistic developer knowledge base from scratch, wire up wiki-links and markdown links into a directed graph, and then walk through every major IWE operation: fuzzy search with find, context-aware retrieval with retrieve, hierarchy display with tree, document consolidation with squash, statistics with stats, […]

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Deep Reinforcement Learning (DRL) is widely recognized as sample-inefficient, a limitation attributable in part to the high dimensionality and substantial functional redundancy inherent to the policy parameter space. A recent framework, which we refer to as Action-based Policy Compression (APC), mitigates this issue by compressing the parameter space $Θ$ into a low-dimensional latent manifold $mathcal Z$ using a learned generative mapping $g:mathcal Z to Θ$. However, its performance is severely constrained by relying on immediate action-matching as a […]

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This work presents a lightweight super-resolution (LiteSR) neural network for depth and intensity images acquired from a consumer-grade single-photon avalanche diode (SPAD) array with a 48×32 spatial resolution. The proposed framework reconstructs high-resolution (HR) images of size 256×256. Both synthetic and real datasets are used for performance evaluation. Extensive quantitative metrics demonstrate high reconstruction fidelity on synthetic datasets, while experiments on real indoor and outdoor measurements further confirm the robustness of the proposed approach. Moreover, the SPAD sensor […]

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FWIW, IANDBL, TINLA, etc., I don’t currently see any basis for concluding that chardet 7.0.0 is required to be released under the LGPL. AFAIK no one including Mark Pilgrim has identified persistence of copyrightable expressive material from earlier versions in 7.0.0 nor has anyone articulated some viable alternate theory of license violation. […] — Richard Fontana, LGPLv3 co-author, weighing in on the chardet relicensing situation Tags: open-source, ai-ethics, llms, ai, generative-ai, ai-assisted-programming

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