Tootfinder

Measurement of Downward-going Milli-charged particles beyond GZK cutoff at the Pierre Auger Observatory
Ye Xu
https://arxiv.org/abs/2506.07395 https://

Measurement of Downward-going Milli-charged particles beyond GZK cutoff at the Pierre Auger Observatory
It is assumed that superheavy dark matter particles (SHDM, $ϕ$) with $\mathcal{O}$(ZeV) mass may decay to relativistic milli-charged particles (MCPs, $χ$) via a channel $ϕ\toχ\barχ$ or $γχ\barχ$. The downward-going MCPs passing through the atmosphere can be measured by the Pierre Auger observatory (Auger). The massless hidden photon model is taken for MCPs to interact with nuclei, so that we evaluated the numbers and fluxes of expected MCPs at Auger assuming 14 years of Auger data. The …

#airtravel is so aggro the last few years. At least in the US. Witnessed 2 outbursts between passengers already and I’m still on the tarmac. Can nobody be nice and just try to chill?

Pushing the Limits of Beam Search Decoding for Transducer-based ASR models
Lilit Grigoryan, Vladimir Bataev, Andrei Andrusenko, Hainan Xu, Vitaly Lavrukhin, Boris Ginsburg
https://arxiv.org/abs/2506.00185

Pushing the Limits of Beam Search Decoding for Transducer-based ASR models
Transducer models have emerged as a promising choice for end-to-end ASR systems, offering a balanced trade-off between recognition accuracy, streaming capabilities, and inference speed in greedy decoding. However, beam search significantly slows down Transducers due to repeated evaluations of key network components, limiting practical applications. This paper introduces a universal method to accelerate beam search for Transducers, enabling the implementation of two optimized algorithms: ALSD++ …

This https://arxiv.org/abs/2501.15056 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Feedback-Aware Monte Carlo Tree Search for Efficient Information Seeking in Goal-Oriented Conversations
Effective decision-making and problem-solving in conversational systems require the ability to identify and acquire missing information through targeted questioning. A key challenge lies in efficiently narrowing down a large space of possible outcomes by posing questions that minimize uncertainty. To address this, we introduce a novel framework that leverages Large Language Models (LLMs) to generate information-seeking questions, with Monte Carlo Tree Search (MCTS) to strategically select quest…

fftvis: A Non-Uniform Fast Fourier Transform Based Interferometric Visibility Simulator
Tyler A. Cox, Steven G. Murray, Aaron R. Parsons, Joshua S. Dillon, Kartik Mandar, Zachary E. Martinot, Robert Pascua, Piyanat Kittiwisit, James E. Aguirre
#toXiv_bot_toot

Effective Versions of Strong Measure Zero
Matthew Rayman
#toXiv_bot_toot

🚀 Melhoramos nossa implementação de malloc(), agora garantindo alinhamento de memória para evitar desperdício e melhorar a performance. Pequenos ajustes, grandes impactos! Quer entender como isso funciona e por que faz diferença? Confira no post 👇
https://suspensao.blog.br/descrenca…

Implementando malloc() e free() — alinhamento de memória
Nossa implementação de malloc() e free() avançou bastante. No último post, vimos por exemplo como unificar blocos de memória menores para evitar fragmentação. Para evitar ainda mais problemas nessa…