Tootfinder

The Coconut Story
Join us on a whimsical journey with nine adventurous coconuts, each with their own unique personality...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/the-coconut-story/

Trump confirms secondary physical included MRI, cognitive test (Julia Manchester/The Hill)
https://thehill.com/homenews/administration/5574520-trump-mri-cognitive-test/
http://www.memeorandum.com/251027/p33#a251027p33

11Plus-Bench: Demystifying Multimodal LLM Spatial Reasoning with Cognitive-Inspired Analysis
Chengzu Li, Wenshan Wu, Huanyu Zhang, Qingtao Li, Zeyu Gao, Yan Xia, Jos\'e Hern\'andez-Orallo, Ivan Vuli\'c, Furu Wei
https://arxiv.org/abs/2508.20068

11Plus-Bench: Demystifying Multimodal LLM Spatial Reasoning with Cognitive-Inspired Analysis
For human cognitive process, spatial reasoning and perception are closely entangled, yet the nature of this interplay remains underexplored in the evaluation of multimodal large language models (MLLMs). While recent MLLM advancements show impressive performance on reasoning, their capacity for human-like spatial cognition remains an open question. In this work, we introduce a systematic evaluation framework to assess the spatial reasoning abilities of state-of-the-art MLLMs relative to human pe…

Cognitive Load Limits in Large Language Models: Benchmarking Multi-Hop Reasoning
Sai Teja Reddy Adapala
https://arxiv.org/abs/2509.19517 https://arxiv.org/…

Cognitive Load Limits in Large Language Models: Benchmarking Multi-Hop Reasoning
The scaling of Large Language Models (LLMs) has exposed a critical gap between their performance on static benchmarks and their fragility in dynamic, information-rich environments. While models excel at isolated tasks, the computational limits that govern their reasoning under cognitive load remain poorly understood. In this work, we introduce a formal theory of computational cognitive load, positing that extraneous, task-irrelevant information (Context Saturation) and interference from task-sw…

Learning to Look: Cognitive Attention Alignment with Vision-Language Models
Ryan L. Yang, Dipkamal Bhusal, Nidhi Rastogi
https://arxiv.org/abs/2509.21247 https://

Learning to Look: Cognitive Attention Alignment with Vision-Language Models
Convolutional Neural Networks (CNNs) frequently "cheat" by exploiting superficial correlations, raising concerns about whether they make predictions for the right reasons. Inspired by cognitive science, which highlights the role of attention in robust human perception, recent methods have sought to guide model attention using concept-based supervision and explanation regularization. However, these techniques depend on labor-intensive, expert-provided annotations, limiting their scalability. We …

More than a feeling: Expressive style influences cortical speech tracking in subjective cognitive decline
Matthew King-Hang Ma, Manson Cheuk-Man Fong, Yun Feng, Cloris Pui-Hang Li, William Shiyuan Wang
https://arxiv.org/abs/2509.21277

More than a feeling: Expressive style influences cortical speech tracking in subjective cognitive decline
Subjective cognitive decline (SCD) approximately doubles the risk of progressing to MCI and dementia. The present study investigates how one's subjective concerns of his/her own cognition are manifested in the neural dynamics during speech perception. EEG was collected from 56 Cantonese, cognitively normal older adults (aged 60 - 70) while they listened to stimuli of four expressive styles that varied in prosody: scrambled, descriptive, dialogue, and exciting. Using encoding models to predict E…

Surprise ... "engineers who allegedly used AI to write a code snippet were perceived as less competent than those who didn’t (and female engineers were disproportionately penalized).
https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity

AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and colla…

🇺🇦 Auf radioeins läuft...
Kid Creole & The Coconuts:
🎵 Stool Pigeon
#NowPlaying #KidCreole #TheCoconuts
https://editlab.bandcamp.com/track/kid-creole-the-coconuts-stool-pigeon-revibelab
https://open.spotify.com/track/6ORoJZ2ghHkOXSBpLwns0N

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Cognitive Load Limits in Large Language Models: Benchmarking Multi-Hop Reasoning
Sai Teja Reddy Adapala
https://arxiv.org/abs/2509.19517 https://arxiv.org/…

Cognitive Load Limits in Large Language Models: Benchmarking Multi-Hop Reasoning
The scaling of Large Language Models (LLMs) has exposed a critical gap between their performance on static benchmarks and their fragility in dynamic, information-rich environments. While models excel at isolated tasks, the computational limits that govern their reasoning under cognitive load remain poorly understood. In this work, we introduce a formal theory of computational cognitive load, positing that extraneous, task-irrelevant information (Context Saturation) and interference from task-sw…