Tootfinder

Jamal Adams reunites with Pete Carroll and signs with Las Vegas Raiders https://www.usatoday.com/story/sports/nfl/2025/07/22/jamal-adams-signs-las-vegas-raiders/85331413007/

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
Chao Yu, Yuanqing Wang, Zhen Guo, Hao Lin, Si Xu, Hongzhi Zang, Quanlu Zhang, Yongji Wu, Chunyang Zhu, Junhao Hu, Zixiao Huang, Mingjie Wei, Yuqing Xie, Ke Yang, Bo Dai, Zhexuan Xu, Xiangyuan Wang, Xu Fu, Zhihao Liu, Kang Chen, Weilin Liu, Gang Liu, Boxun Li, Jianlei Yang, Zhi Yang, Guohao Dai, Yu Wang

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
Reinforcement learning (RL) has demonstrated immense potential in advancing artificial general intelligence, agentic intelligence, and embodied intelligence. However, the inherent heterogeneity and dynamicity of RL workflows often lead to low hardware utilization and slow training on existing systems. In this paper, we present RLinf, a high-performance RL training system based on our key observation that the major roadblock to efficient RL training lies in system flexibility. To maximize flexib…

Beyond Architectures: Evaluating the Role of Contextual Embeddings in Detecting Bipolar Disorder on Social Media
Khalid Hasan, Jamil Saquer
https://arxiv.org/abs/2507.14231

Beyond Architectures: Evaluating the Role of Contextual Embeddings in Detecting Bipolar Disorder on Social Media
Bipolar disorder is a chronic mental illness frequently underdiagnosed due to subtle early symptoms and social stigma. This paper explores the advanced natural language processing (NLP) models for recognizing signs of bipolar disorder based on user-generated social media text. We conduct a comprehensive evaluation of transformer-based models (BERT, RoBERTa, ALBERT, ELECTRA, DistilBERT) and Long Short Term Memory (LSTM) models based on contextualized (BERT) and static (GloVe, Word2Vec) word embe…

MOHAF: A Multi-Objective Hierarchical Auction Framework for Scalable and Fair Resource Allocation in IoT Ecosystems
Kushagra Agrawal, Polat Goktas, Anjan Bandopadhyay, Debolina Ghosh, Junali Jasmine Jena, Mahendra Kumar Gourisaria
https://arxiv.org/abs/2508.14830

MOHAF: A Multi-Objective Hierarchical Auction Framework for Scalable and Fair Resource Allocation in IoT Ecosystems
The rapid growth of Internet of Things (IoT) ecosystems has intensified the challenge of efficiently allocating heterogeneous resources in highly dynamic, distributed environments. Conventional centralized mechanisms and single-objective auction models, focusing solely on metrics such as cost minimization or revenue maximization, struggle to deliver balanced system performance. This paper proposes the Multi-Objective Hierarchical Auction Framework (MOHAF), a distributed resource allocation mech…

#NowPlaying the new record M.E.M.O.I.R.S. by Jamil Honesty x JrSwiftz and this is some 🔥
https://jamilhonesty.bandcamp.com/album/m-e-m-o-i-r-s-2

2 former first rounders and a 3-time Pro Bowler among 5 Raiders signings on eve of camp https://raiderswire.usatoday.com/story/sports/nfl/raiders/2025/07/22/pro-bowl-safety-jamal-adams-phil…

Differential constraints for hyperbolic systems through k-Riemann invariants
Alessandra Jannelli, Natale Manganaro, Alessandra Rizzo
https://arxiv.org/abs/2507.14877

Differential constraints for hyperbolic systems through k-Riemann invariants
In this paper we develop a reduction procedure for determining exact wave solutions of first order quasilinear hyperbolic one-dimensional nonhomogeneous systems. The approach is formulated within the theoretical framework of the method of differential constraints and it makes use of the $k-$Riemann invariants. The solutions obtained permit to characterize rarefaction waves also for nonhomogeneous models so that Riemann problems can be solved. Applications to the Euler system describing an ideal…

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
Yuxiao Cheng, Jinli Suo
https://arxiv.org/abs/2509.14778 https://arxiv.org/pdf/2509.1477…

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
Health informatics research is characterized by diverse data modalities, rapid knowledge expansion, and the need to integrate insights across biomedical science, data analytics, and clinical practice. These characteristics make it particularly well-suited for agent-based approaches that can automate knowledge exploration, manage complex workflows, and generate clinically meaningful outputs. Recent progress in large language model (LLM)-based agents has demonstrated promising capabilities in lit…

jXBW: Fast Substructure Search in Large-Scale JSONL Datasets for Foundation Model Applications
Yasuo Tabei
https://arxiv.org/abs/2508.12536 https://arxiv.o…

jXBW: Fast Substructure Search in Large-Scale JSONL Datasets for Foundation Model Applications
Substructure search in JSON Lines (JSONL) datasets is essential for modern applications such as prompt engineering in foundation models, but existing methods suffer from prohibitive computational costs due to exhaustive tree traversal and subtree matching. We present jXBW, a fast method for substructure search on large-scale JSONL datasets. Our method makes three key technical contributions: (i) a merged tree representation built by merging trees of multiple JSON objects while preserving indivi…

Beyond Physicians: Social and Familial Norms Driving Cesarean Section Decisions in Bangladesh
Jamal Uddin
https://arxiv.org/abs/2508.12240 https://arxiv.or…

Beyond Physicians: Social and Familial Norms Driving Cesarean Section Decisions in Bangladesh
Women's health in Bangladesh faces risks due to an alarming rise in cesarean section (CS) rates, exceeding 72% in hospital-based deliveries, far surpassing the WHO's recommended limit of 15%. This study, guided by the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB), explored socio-cultural factors influencing childbirth mode decisions. Among 503 survey participants, 91% of CS cases occurred against initial preferences, revealing a disconnect between health beliefs and behavio…