Tootfinder

DPRK and Russia are deepening cooperation! The danger of a new conflict is growing #shorts: https://benborges.xyz/2025/07/03/dprk-and-russia-are-deepening.html

the internet peaked with allie brosh. it's been downhill ever since.. https://www.motherjones.com/media/2013/10/allie-brosh-hyperbole-half-book-depression/

Meet the creator of the cartoon blog (and new book) "Hyperbole and a Half"
Allie Brosh turns her childhood memories and struggles with depression into irresistable reading.

ALMA Reveals an Eccentricity Gradient in the Fomalhaut Debris Disk / High Resolution ALMA Data of the #Fomalhaut Debris Disk Confirms Apsidal Width Variation: https://arxiv.org/abs/2509.02884 / https://arxiv.org/abs/2509.02825 -> Neighboring Star’s Warped Ring Shaped by Evolving Planets: https://public.nrao.edu/news/neighboring-stars-warped-ring-shaped-by-evolving-planets/ - unusual shape of Fomalhaut’s debris ring shows evidence of sculpting by ancient planets, rewriting story of planetary system evolution.

Towards Multi-Aspect Diversification of News Recommendations Using Neuro-Symbolic AI for Individual and Societal Benefit
Markus Reiter-Haas, Elisabeth Lex
https://arxiv.org/abs/2509.02220

Towards Multi-Aspect Diversification of News Recommendations Using Neuro-Symbolic AI for Individual and Societal Benefit
News recommendations are complex, with diversity playing a vital role. So far, existing literature predominantly focuses on specific aspects of news diversity, such as viewpoints. In this paper, we introduce multi-aspect diversification in four distinct recommendation modes and outline the nuanced challenges in diversifying lists, sequences, summaries, and interactions. Our proposed research direction combines symbolic and subsymbolic artificial intelligence, leveraging both knowledge graphs an…

Data Diversification Methods In Alignment Enhance Math Performance In LLMs
Berkan Dokmeci, Qingyang Wu, Ben Athiwaratkun, Ce Zhang, Shuaiwen Leon Song, James Zou
https://arxiv.org/abs/2507.02173

Data Diversification Methods In Alignment Enhance Math Performance In LLMs
While recent advances in preference learning have enhanced alignment in human feedback, mathematical reasoning remains a persistent challenge. We investigate how data diversification strategies in preference optimization can improve the mathematical reasoning abilities of large language models (LLMs). We evaluate three common data generation methods: temperature sampling, Chain-of-Thought prompting, and Monte Carlo Tree Search (MCTS), and introduce Diversified-ThinkSolve (DTS), a novel structur…

Jointly Reinforcing Diversity and Quality in Language Model Generations
Tianjian Li, Yiming Zhang, Ping Yu, Swarnadeep Saha, Daniel Khashabi, Jason Weston, Jack Lanchantin, Tianlu Wang
https://arxiv.org/abs/2509.02534

Jointly Reinforcing Diversity and Quality in Language Model Generations
Post-training of Large Language Models (LMs) often prioritizes accuracy and helpfulness at the expense of diversity. This creates a tension: while post-training improves response quality, it also sharpens output distributions and reduces the range of ideas, limiting the usefulness of LMs in creative and exploratory tasks such as brainstorming, storytelling, or problem solving. We address this challenge with Diversity-Aware Reinforcement Learning (DARLING), a framework that jointly optimizes for…

Dat lijkt me geheel terecht
Florida family files claim with NASA after ISS space junk crashes into home | Space
https://www.space.com/space-debris-florida-family-nasa-lawsuit

It's amazing to me that people continue to look back at 2024 and angrily blame muslims,non-voters, & leftists for the overwhelming win by Trump. It must be nice to be able to completely ignore reality and learn nothing.
https://www.

Behind Trump’s 2024 Victory, a More Racially and Ethnically Diverse Voter Coalition
Pew Research Center’s in-depth study of its survey respondents who voted in the 2024 election examines turnout, voting patterns and demographics.

Avoidance Decoding for Diverse Multi-Branch Story Generation
Kyeongman Park, Nakyeong Yang, Kyomin Jung
https://arxiv.org/abs/2509.02170 https://arxiv.org/…

Avoidance Decoding for Diverse Multi-Branch Story Generation
Large Language Models (LLMs) often generate repetitive and monotonous outputs, especially in tasks like story generation, due to limited creative diversity when given the same input prompt. To address this challenge, we propose a novel decoding strategy, Avoidance Decoding, that modifies token logits by penalizing similarity to previously generated outputs, thereby encouraging more diverse multi-branch stories. This penalty adaptively balances two similarity measures: (1) Concept-level Similari…

Multimodal Mathematical Reasoning with Diverse Solving Perspective
Wenhao Shi, Zhiqiang Hu, Yi Bin, Yang Yang, See-Kiong Ng, Heng Tao Shen
https://arxiv.org/abs/2507.02804

Multimodal Mathematical Reasoning with Diverse Solving Perspective
Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capabilities of large language models (LLMs), especially in mathematical domains. However, current multimodal LLMs (MLLMs) for mathematical reasoning often rely on one-to-one image-text pairs and single-solution supervision, overlooking the diversity of valid reasoning perspectives and internal reflections. In this work, we introduce MathV-DP, a novel dataset that captures multiple diverse solution tra…