Tootfinder

Batched Adaptive Network Formation
Yan Xu, Bo Zhou
https://arxiv.org/abs/2507.18961 https://arxiv.org/pdf/2507.18961

Batched Adaptive Network Formation
Networks are central to many economic and organizational applications, including workplace team formation, social platform recommendations, and classroom friendship development. In these settings, networks are modeled as graphs, with agents as nodes, agent pairs as edges, and edge weights capturing pairwise production or interaction outcomes. This paper develops an adaptive, or \textit{online}, policy that learns to form increasingly effective networks as data accumulates over time, progressive…

This https://arxiv.org/abs/2505.04555 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Who Bears the Cost? High-Frequency Evidence on Minimum Wage Effects and Amenity Pass-Through in Spot Labor Markets
This paper provides causal evidence on the short-run effects of minimum wage hikes in a spot labor market, using confidential contract-level data from Timee, a Japanese job-matching platform. Leveraging high-frequency variation and a bin-level difference-in-differences design, we find a 2 percentage point decline in employment within affected wage bins, with losses concentrated below the new threshold. Transportation reimbursement--a flexible nonwage amenity--remains largely unchanged, indicati…

Blaine Cook, an original Twitter architect is one of the backers of the new Canadian social platform #Gander
https://www.theglobeandmail.com/busi…

Tech leaders ready launch of Canadian social-media platform Gander to buck U.S. dominance
Founders aim to create alternative that addresses content, data sovereignty concerns

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem
Mohammad Shahedur Rahman, Peng Gao, Yuede Ji
https://arxiv.org/abs/2507.14240 https://…

HuggingGraph: Understanding the Supply Chain of LLM Ecosystem
Large language models (LLMs) leverage deep learning to process and predict sequences of words from context, enabling them to perform various NLP tasks, such as translation, summarization, question answering, and content generation. However, the growing size and complexity of developing, training, and deploying advanced LLMs require extensive computational resources and large datasets. This creates a barrier for users. As a result, platforms that host models and datasets are widely used. For exa…

Dzięki @… za przypomnienie mi o tej wspaniałej platformówce sprzed lat!

Od razu kupiłem na gog i zainstalowałem z z flatpacka wersje na stemadecka.

Z chęcią kiedyś zagram w poziom, który budujesz :D

#giereczkowo …

Forbes reshuffles its leadership team and forms an AI & Strategic Platforms Group to identify future revenue streams and grow its brand across social platforms (Chris Roush/Talking Biz News)
https://talkingbiznews.com/media-news/forbes-shuffles-le…

Forbes shuffles leadership, aiming for more growth - Talking Biz News
Forbes announced changes to its leadership on Monday, looking to boost its future growth and artificial intelligence opportunities. Nina Gould was promoted to chief innovation officer, overseeing Forbes’ technology and product businesses. She will oversee Forbes’ technology, product and product design, data and business intelligence, audience growth and development, accolades and eCommerce businesses and brand […]

Building a Media Ecosystem Observatory from Scratch: Infrastructure, Methodology, and Insights
Zeynep Pehlivan, Saewon Park, Alexei Sisulu Abrahams, Mika Desblancs-Patel, Benjamin David Steel, Aengus Bridgman
https://arxiv.org/abs/2506.10942

Building a Media Ecosystem Observatory from Scratch: Infrastructure, Methodology, and Insights
Understanding the flow of information across today's fragmented digital media landscape requires scalable, cross-platform infrastructure. In this paper, we present the Canadian Media Ecosystem Observatory, a national-scale infrastructure designed to monitor political and media discourse across platforms in near real time. Media Ecosystem Observatory (MEO) data infrastructure features custom crawlers for major platforms, a unified indexing pipeline, and a normalization layer that harmonizes he…

RSD-15K: A Large-Scale User-Level Annotated Dataset for Suicide Risk Detection on Social Media
Shouwen Zheng, Yingzhi Tao, Taiqi Zhou
https://arxiv.org/abs/2507.11559

RSD-15K: A Large-Scale User-Level Annotated Dataset for Suicide Risk Detection on Social Media
In recent years, cognitive and mental health (CMH) disorders have increasingly become an important challenge for global public health, especially the suicide problem caused by multiple factors such as social competition, economic pressure and interpersonal relationships among young and middle-aged people. Social media, as an important platform for individuals to express emotions and seek help, provides the possibility for early detection and intervention of suicide risk. This paper introduces a…

Understanding Online Polarization Through Human-Agent Interaction in a Synthetic LLM-Based Social Network
Tim Donkers, J\"urgen Ziegler
https://arxiv.org/abs/2506.15866

Understanding Online Polarization Through Human-Agent Interaction in a Synthetic LLM-Based Social Network
The rise of social media has fundamentally transformed how people engage in public discourse and form opinions. While these platforms offer unprecedented opportunities for democratic engagement, they have been implicated in increasing social polarization and the formation of ideological echo chambers. Previous research has primarily relied on observational studies of social media data or theoretical modeling approaches, leaving a significant gap in our understanding of how individuals respond t…

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration
Jiaqi Lv, Xufeng He, Yanchen Liu, Xu Dai, Yang Hu, Shouyi Yin
https://arxiv.org/abs/2506.10401

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration
The rapid growth of deep learning has driven exponential increases in model parameters and computational demands. NVIDIA GPUs and their CUDA-based software ecosystem provide robust support for parallel computing, significantly alleviating computational bottlenecks. Meanwhile, due to the cultivation of user programming habits and the high performance of GPUs, the CUDA ecosystem has established a dominant position in the field of parallel software. This dominance requires other hardware platforms…