Posts
All the articles I've posted.
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Single-shot prediction of parametric partial differential equations
Flexi-VAE introduces a variational autoencoder framework for single-shot forecasting of parametric PDEs, using a neural propagator to achieve efficient, accurate long-horizon predictions with significant speedups over sequential models like AE-LSTM, as validated on Burgers' and advection-diffusion equations.
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AI in Money Matters
This paper investigates the cautious adoption of Large Language Models like ChatGPT in the Fintech industry through qualitative interviews, highlighting professionals' optimism for routine task automation, concerns over regulatory inadequacies, and interest in bespoke models to ensure compliance and data control.
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A Statistical Case Against Empirical Human-AI Alignment
This position paper argues against forward empirical human-AI alignment due to statistical biases and anthropocentric limitations, advocating for prescriptive and backward alignment approaches to ensure transparency and minimize bias, supported by a case study on language model decoding strategies.
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Purity Law for Generalizable Neural TSP Solvers
This paper introduces Purity Law (PuLa), a structural principle revealing sparsity bias in optimal TSP solutions, and proposes Purity Policy Optimization (PUPO), a training framework that significantly enhances the generalization of neural TSP solvers across diverse scales and distributions without inference overhead.
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Belief Injection for Epistemic Control in Linguistic State Space
This paper proposes belief injection as a proactive epistemic control mechanism to shape AI agents' internal linguistic belief states within the Semantic Manifold framework, offering diverse strategies for guiding reasoning and alignment, though it lacks empirical validation.