XR Blocks supplies an LLM-optimized Reality Model and Vibe Coding XR workflow that converts high-level prompts into working physics-aware XR applications with high one-shot success.
Gomez, Łukasz Kaiser, and Illia Polosukhin
8 Pith papers cite this work. Polarity classification is still indexing.
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NES systems in AI IDEs expand attack surfaces via context poisoning from imperceptible actions and global codebase retrieval, with professional developers largely unaware of the risks.
Mamba-Assisted Closure (MAC) trains a Mamba sequence model on resolved trajectories to predict non-Markovian closures and couples it with reduced-order equations, outperforming Markovian, GRU, and Wilks baselines on Burgers' and Lorenz '96 systems.
A survey and benchmark of ~60 PSD algorithms on two radiation datasets finds deep learning models (MLPs and hybrids) often outperform traditional statistical methods, with an open-source Python/MATLAB toolbox and datasets released.
A multimodal domain-adversarial network fuses silicon tracker and time-of-flight data with domain-invariant training to suppress fragmentation backgrounds in AMS heavy nuclei flux measurements, demonstrated on phosphorus using Monte Carlo training.
Rulemapping uses expert symbolic scaffolds to constrain LLMs, raising precision on §130(1) German hate-speech classification from 0.34-0.49 to 0.80-0.86 while preserving recall of 0.82-0.89.
Council Mode reduces LLM hallucinations by 35.9% and improves TruthfulQA scores by 7.8 points through parallel heterogeneous model generation followed by structured consensus synthesis.
Tensor networks developed for quantum states are reviewed as tools for machine learning models, with assessment of their potential computational, explanatory, and privacy advantages alongside remaining challenges.
citing papers explorer
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"Tab, Tab, Bug": Security Pitfalls of Next Edit Suggestions in AI-Integrated IDEs
NES systems in AI IDEs expand attack surfaces via context poisoning from imperceptible actions and global codebase retrieval, with professional developers largely unaware of the risks.