Tootfinder

Chiefs WR Rashee Rice cooperating with authorities following reported crash, lawyer says https://www.nfl.com/news/chiefs-wr-rashee-rice-cooperating-with-authorities-following-reported-crash-lawyer-says

Chiefs WR Rashee Rice cooperating with authorities following reported crash, lawyer says
A lawyer for Kanas City Chiefs wide receiver Rashee Rice said on Monday that Rice "is cooperating with authorities" after a report of a multi-vehicle crash this past weekend in Dallas involving a car associated with Rice.

A Multi-agent Reinforcement Learning Study of Evolution of Communication and Teaching under Libertarian and Utilitarian Governing Systems
Aslan S. Dizaji
https://arxiv.org/abs/2403.02369

A Multi-agent Reinforcement Learning Study of Evolution of Communication and Teaching under Libertarian and Utilitarian Governing Systems
Laboratory experiments have shown that communication plays an important role in solving social dilemmas. Here, by extending the AI-Economist, a mixed motive multi-agent reinforcement learning environment, I intend to find an answer to the following descriptive question: which governing system does facilitate the emergence and evolution of communication and teaching among agents? To answer this question, the AI-Economist is extended by a voting mechanism to simulate three different governing sys…

Corral Some Zippy Blue Flames Into 3D Printed Troughs
https://poliverso.org/display/0477a01e-237504d0-e7bf32edd4324f0e
Corral Some Zippy Blue Flames Into 3D Printed Troughs [Steve Mould] came across an interesting little phenomenon of blue flames zi…

Reversible single-pulse laser-induced phase change of Sb$_2$S$_3$ thin films: multi-physics modeling and experimental demonstrations
Capucine Laprais, Cl\'ement Zrounba, Julien Bouvier, Nicholas Blanchard, Matthieu Bugnet, Yael Guti\'errez, Saul Vazquez-Miranda, Shirly Espinoza, Peter Thiesen, Romain Bourrellier, Aziz Benamrouche, Nicolas Baboux, Guillaume Saint-Girons, Lotfi Berguiga, S\'ebastien Cueff

Reversible single-pulse laser-induced phase change of Sb$_2$S$_3$ thin films: multi-physics modeling and experimental demonstrations
Phase change materials (PCMs) have gained a tremendous interest as a means to actively tune nanophotonic devices through the large optical modulation produced by their amorphous to crystalline reversible transition. Recently, materials such as Sb$_2$S$_3$ emerged as particularly promising low loss PCMs, with both large refractive index modulations and transparency in the visible and NIR. Controlling the local and reversible phase transition in this material is of major importance for future app…

Military intelligence: Russia flies attack drones over occupied Zaporizhzhia plant, video shows: https://benborges.xyz/2024/05/02/military-intelligence-russia.html

Master equations with indefinite nonlinearities
Wenxiong Chen, Yahong Guo
https://arxiv.org/abs/2405.02091 https://arxiv.org/pdf/2405…

Master equations with indefinite nonlinearities
In this paper, we consider the following indefinite fully fractional heat equation involving the master operator \begin{equation*} (\partial_t -Δ)^{s} u(x,t) = x_1u^p(x,t)\ \ \mbox{in}\ \R^n\times\R , \end{equation*} where $s\in(0,1)$, and $-\infty < p < \infty$. Under mild conditions, we prove that there is no positive bounded solutions. To this end, we first show that the solutions are strictly increasing along $x_1$ direction by employing the direct method of moving planes. Then by construc…

Multi-intent-aware Session-based Recommendation
Minjin Choi, Hye-young Kim, Hyunsouk Cho, Jongwuk Lee
https://arxiv.org/abs/2405.00986 https://

Multi-intent-aware Session-based Recommendation
Session-based recommendation (SBR) aims to predict the following item a user will interact with during an ongoing session. Most existing SBR models focus on designing sophisticated neural-based encoders to learn a session representation, capturing the relationship among session items. However, they tend to focus on the last item, neglecting diverse user intents that may exist within a session. This limitation leads to significant performance drops, especially for longer sessions. To address thi…

This https://arxiv.org/abs/2403.11893 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum Coordination Rates in Multi-Partite Networks
The optimal coordination rates are determined in three primary settings of multi-partite quantum networks, thus characterizing the minimal resources required in order to simulate a joint quantum state among multiple parties. We study the following models: (1) a cascade network with limited entanglement, (2) a broadcast network, which consists of a single sender and two receivers, (3) a multiple-access network with two senders and a single receiver. We establish the necessary and sufficient cond…

Better & Faster Large Language Models via Multi-token Prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozi\`ere, David Lopez-Paz, Gabriel Synnaeve
https://arxiv.org/abs/2404.19737 https://arxiv.org/pdf/2404.19737
arXiv:2404.19737v1 Announce Type: new
Abstract: Large language models such as GPT and Llama are trained with a next-token prediction loss. In this work, we suggest that training language models to predict multiple future tokens at once results in higher sample efficiency. More specifically, at each position in the training corpus, we ask the model to predict the following n tokens using n independent output heads, operating on top of a shared model trunk. Considering multi-token prediction as an auxiliary training task, we measure improved downstream capabilities with no overhead in training time for both code and natural language models. The method is increasingly useful for larger model sizes, and keeps its appeal when training for multiple epochs. Gains are especially pronounced on generative benchmarks like coding, where our models consistently outperform strong baselines by several percentage points. Our 13B parameter models solves 12 % more problems on HumanEval and 17 % more on MBPP than comparable next-token models. Experiments on small algorithmic tasks demonstrate that multi-token prediction is favorable for the development of induction heads and algorithmic reasoning capabilities. As an additional benefit, models trained with 4-token prediction are up to 3 times faster at inference, even with large batch sizes.

Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model
Wentao Ouyang, Xiuwu Zhang, Chaofeng Guo, Shukui Ren, Yupei Sui, Kun Zhang, Jinmei Luo, Yunfeng Chen, Dongbo Xu, Xiangzheng Liu, Yanlong Du
https://arxiv.org/abs/2403.17425

Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model
In real-world advertising systems, conversions have different types in nature and ads can be shown in different display scenarios, both of which highly impact the actual conversion rate (CVR). This results in the multi-type and multi-scenario CVR prediction problem. A desired model for this problem should satisfy the following requirements: 1) Accuracy: the model should achieve fine-grained accuracy with respect to any conversion type in any display scenario. 2) Scalability: the model parameter…