Tootfinder

https://www.instagram.com/p/DSbtXuCCe9Y/?utm_source=ig_web_copy_link&igsh=NTc4MTIwNjQ2YQ==

Japan Daily on Instagram: "Marty Friedman, an American musician based in Japan, visited a junior high school in Chiba at an event organized by local police to promote coexistence with foreigners. Speaking to first-year students, he said that 99.9% of foreigners who come to Japan are not dangerous and are often eager to communicate with Japanese people. He encouraged students to learn foreign languages and approach others without fear. Friedman also shared a personal story about forgetting his wallet in Japan, highlighting the country’s honesty. The event aimed to help young people understand cultural differences as foreign visitors and workers increase. Learning with empathy can reduce tension and improve everyday interactions. Source:TOKYO NP"
2,062 likes, 113 comments - japandaily_jp on December 18, 2025: "Marty Friedman, an American musician based in Japan, visited a junior high school in Chiba at an event organized by local police to promote coexistence with foreigners. Speaking to first-year students, he said that 99.9% of foreigners who come to Japan are not dangerous and are often eager to communicate with Japanese people. He encouraged students to learn foreign languages and approach others without fear. Friedman also shar…

I think there is just as much chance of Half-Life 3 launching as there is of the rapture happening. Plot twist: I don’t see either happening.
https://www.ign.com/articles/why-is-everyone-posting-about-a-half-life-3-announcement-soon

It's fascinating that we largely went from a network of personal computers processing data locally that could access an open hypertext system linking together millions of websites…
…to phones with proprietary closed apps that often largely are little more than little windows to timesharing mainframes.

Token-Level Policy Optimization: Linking Group-Level Rewards to Token-Level Aggregation via Markov Likelihood
Xingyu Lin, Yilin Wen, En Wang, Du Su, Wenbin Liu, Chenfu Bao, Zhonghou Lv
https://arxiv.org/abs/2510.09369

Token-Level Policy Optimization: Linking Group-Level Rewards to Token-Level Aggregation via Markov Likelihood
Group Relative Policy Optimization (GRPO) has significantly advanced the reasoning ability of large language models (LLMs), particularly by boosting their mathematical performance. However, GRPO and related entropy-regularization methods still face challenges rooted in the sparse token rewards inherent to chain-of-thought (CoT). Current approaches often rely on undifferentiated token-level entropy adjustments, which frequently lead to entropy collapse or model collapse. In this work, we propose…

this looks really great: "Metropolitans: New York Baseball, Class Struggle, and the People's Team"
https://www.skylightbooks.com/book/9781662603006 via @…

Metropolitans: New York Baseball, Class Struggle, and the People's Team (Hardcover) | Skylight Books
“Metropolitans expertly unpacks the 'cruel optimism' linking the yearning of a fanbase whose suffering is alleviated by sporadic miracles to the genuine dissident legacies that surrounded the team's creation and which have occasionally, miraculously, come back to life." —Jonathan Lethem, author of Motherless Brooklyn and The Fortress of SolitudeA love letter to a franchise and a thrill

Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
Othman Cherkaoui Dekkaki
https://arxiv.org/abs/2510.11381 https://arxiv.org/pd…

Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
We develop an optimal control model for allocating agricultural crop residues between bioenergy production and soil fertility restoration. The system captures a novel circular feedback: a fraction of cumulative energy output is reinvested into soil productivity, linking energy use with ecological regeneration. The dynamics are governed by a nonlinear three-state system describing soil fertility, residue biomass, and accumulated energy, with a single control representing the proportion of biomas…

Fast and Interpretable Protein Substructure Alignment via Optimal Transport
Zhiyu Wang, Bingxin Zhou, Jing Wang, Yang Tan, Weishu Zhao, Pietro Li\`o, Liang Hong
https://arxiv.org/abs/2510.11752

Fast and Interpretable Protein Substructure Alignment via Optimal Transport
Proteins are essential biological macromolecules that execute life functions. Local motifs within protein structures, such as active sites, are the most critical components for linking structure to function and are key to understanding protein evolution and enabling protein engineering. Existing computational methods struggle to identify and compare these local structures, which leaves a significant gap in understanding protein structures and harnessing their functions. This study presents PLAS…

Secret-Protected Evolution for Differentially Private Synthetic Text Generation
Tianze Wang, Zhaoyu Chen, Jian Du, Yingtai Xiao, Linjun Zhang, Qiang Yan
https://arxiv.org/abs/2510.10990

Secret-Protected Evolution for Differentially Private Synthetic Text Generation
Text data has become extremely valuable on large language models (LLMs) and even lead to general artificial intelligence (AGI). A lot of high-quality text in the real world is private and cannot be freely used due to privacy concerns. Therefore, differentially private (DP) synthetic text generation has been proposed, aiming to produce high-utility synthetic data while protecting sensitive information. However, existing DP synthetic text generation imposes uniform guarantees that often overprote…

Group Critical-token Policy Optimization for Autoregressive Image Generation
Guohui Zhang, Hu Yu, Xiaoxiao Ma, JingHao Zhang, Yaning Pan, Mingde Yao, Jie Xiao, Linjiang Huang, Feng Zhao
https://arxiv.org/abs/2509.22485

Group Critical-token Policy Optimization for Autoregressive Image Generation
Recent studies have extended Reinforcement Learning with Verifiable Rewards (RLVR) to autoregressive (AR) visual generation and achieved promising progress. However, existing methods typically apply uniform optimization across all image tokens, while the varying contributions of different image tokens for RLVR's training remain unexplored. In fact, the key obstacle lies in how to identify more critical image tokens during AR generation and implement effective token-wise optimization for them. T…