Tootfinder

Revisiting Reliability in the Reasoning-based Pose Estimation Benchmark
Junsu Kim, Naeun Kim, Jaeho Lee, Incheol Park, Dongyoon Han, Seungryul Baek
https://arxiv.org/abs/2507.13314

Revisiting Reliability in the Reasoning-based Pose Estimation Benchmark
The reasoning-based pose estimation (RPE) benchmark has emerged as a widely adopted evaluation standard for pose-aware multimodal large language models (MLLMs). Despite its significance, we identified critical reproducibility and benchmark-quality issues that hinder fair and consistent quantitative evaluations. Most notably, the benchmark utilizes different image indices from those of the original 3DPW dataset, forcing researchers into tedious and error-prone manual matching processes to obtain…

"Musk and his allies systematically built a false narrative of widespread fraud at the Social Security Administration based on misinterpreted data, using their claims to justify an aggressive effort to gain access to personal information on millions of Americans."
Gift link.

Inside DOGE’s Chaotic Takeover of Social Security
The drama offers a case study in how Elon Musk’s team sought to run a critical government agency through misinformation and social media blasts — and how longtime employees responded.

Group Backed by George Soros to Plow Millions Into Turning Texas Blue (Ken Thomas/Wall Street Journal)
https://www.wsj.com/politics/group-backed-by-george-soros-to-plow-millions-into-turning-texas-blue-4dfa75bf
http://www.memeorandum.com/250609/p22#a250609p22

InSight: AI Mobile Screening Tool for Multiple Eye Disease Detection using Multimodal Fusion
Ananya Raghu, Anisha Raghu, Alice S. Tang, Yannis M. Paulus, Tyson N. Kim, Tomiko T. Oskotsky
https://arxiv.org/abs/2507.12669

InSight: AI Mobile Screening Tool for Multiple Eye Disease Detection using Multimodal Fusion
Background/Objectives: Age-related macular degeneration, glaucoma, diabetic retinopathy (DR), diabetic macular edema, and pathological myopia affect hundreds of millions of people worldwide. Early screening for these diseases is essential, yet access to medical care remains limited in low- and middle-income countries as well as in resource-limited settings. We develop InSight, an AI-based app that combines patient metadata with fundus images for accurate diagnosis of five common eye diseases to…

LaSM: Layer-wise Scaling Mechanism for Defending Pop-up Attack on GUI Agents
Zihe Yan, Zhuosheng Zhang
https://arxiv.org/abs/2507.10610 https://

LaSM: Layer-wise Scaling Mechanism for Defending Pop-up Attack on GUI Agents
Graphical user interface (GUI) agents built on multimodal large language models (MLLMs) have recently demonstrated strong decision-making abilities in screen-based interaction tasks. However, they remain highly vulnerable to pop-up-based environmental injection attacks, where malicious visual elements divert model attention and lead to unsafe or incorrect actions. Existing defense methods either require costly retraining or perform poorly under inductive interference. In this work, we systemati…

MLLM-Based UI2Code Automation Guided by UI Layout Information
Fan Wu, Cuiyun Gao, Shuqing Li, Xin-Cheng Wen, Qing Liao
https://arxiv.org/abs/2506.10376 htt…

MLLM-Based UI2Code Automation Guided by UI Layout Information
Converting user interfaces into code (UI2Code) is a crucial step in website development, which is time-consuming and labor-intensive. The automation of UI2Code is essential to streamline this task, beneficial for improving the development efficiency. There exist deep learning-based methods for the task; however, they heavily rely on a large amount of labeled training data and struggle with generalizing to real-world, unseen web page designs. The advent of Multimodal Large Language Models (MLLMs…

fly_larva: Drosophila larva brain (2023)
A complete synaptic map of the brain connectome of the larva of the fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using three-dimensional electron microscopy–based reconstruction. Node metadata include the neuron hempisphere, hemispherical homologue, cell type, annotations, and inferred cluster. Edge metadata include the type of interaction (`'aa'`,…

INTERPOS: Interaction Rhythm Guided Positional Morphing for Mobile App Recommender Systems
M. H. Maqbool, Moghis Fereidouni, Umar Farooq, A. B. Siddique, Hassan Foroosh
https://arxiv.org/abs/2506.12661

INTERPOS: Interaction Rhythm Guided Positional Morphing for Mobile App Recommender Systems
The mobile app market has expanded exponentially, offering millions of apps with diverse functionalities, yet research in mobile app recommendation remains limited. Traditional sequential recommender systems utilize the order of items in users' historical interactions to predict the next item for the users. Position embeddings, well-established in transformer-based architectures for natural language processing tasks, effectively distinguish token positions in sequences. In sequential recommenda…

High Socioeconomic Status is Associated with Diverse Consumption across Brands and Price Levels
Yuanmo He, Milena Tsvetkova
https://arxiv.org/abs/2506.13840

High Socioeconomic Status is Associated with Diverse Consumption across Brands and Price Levels
Consumption practices are determined by a combination of economic, social, and cultural forces. We posit that lower economic constraints leave more room to diversify consumption along cultural and social aspects in the form of omnivorous or lifestyle-based niche consumption. We provide empirical evidence for this diversity hypothesis by analysing millions of mobile-tracked visits from thousands of Census Block Groups to thousands of stores in New York State. The results show that high income is…

ByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way
Rajarshi Roy, Devleena Das, Ankesh Banerjee, Arjya Bhattacharjee, Kousik Dasgupta, Subarna Tripathi
https://arxiv.org/abs/2507.08679

ByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way
We introduce ByDeWay, a training-free framework designed to enhance the performance of Multimodal Large Language Models (MLLMs). ByDeWay uses a novel prompting strategy called Layered-Depth-Based Prompting (LDP), which improves spatial reasoning and grounding without modifying any model parameters. It segments the scene into closest, mid-range, and farthest layers using monocular depth estimation, then generates region-specific captions with a grounded vision-language model. These structured, d…