Tootfinder

The stranger in “Wayfaring” unmasked #becoming #humanbeings https://muz4now.com/2025/the-stranger-

The stranger in "Wayfaring" unmasked
Stan Stewart - @muz4now

Manchmal glaube ich, sowas wie eine Renaissance dunkler Technikgläubigkeit zu sehen - in Computer, KI, Technik wird alles mögliche hineinprojiziert, gerne in sich selbst verstärkenden "kritischen" Kreisen. Auch nicht besser als die technikoptimistische Variante davon.

Heute war #Generalprobe, morgen ist #Premiere.
Für mich waren die vergangenen Wochen ein dauerhafter #Bühnenbau Marathon, aber ab jetzt kann ich auch nur noch zusehen ;)
@…

Radio CORAX (@RadioCORAX@social.anoxinon.de)
Attached: 1 image Theater über Depressionen – ein Gespräch mit Julia Raab Corona-Pandemie, Klimakrise, Krieg, Armut, Leistungsdruck und Lehrkräftemangel in Schulen. Alldem waren und sind Kinder und Jugendliche in den vergangenen Jahren ausgesetzt. Mit Chaos im Kopf umzugehen, fällt oft schon uns Erwachsenen nicht leicht. Wie…... https://radiocorax.de/theater-ueber-depressionen-ein-gespraech-mit-julia-raab/

Pedestrian collision avoidance in hemianopia during natural walking in immersive virtual reality
Jonathan K. Doyon, Sujin Kim, Alex D. Hwang, Jae-Hyun Jung
https://arxiv.org/abs/2510.04218

Pedestrian collision avoidance in hemianopia during natural walking in immersive virtual reality
Homonymous hemianopia (HH) patients report difficulties in avoiding collisions with other pedestrians. We evaluated pedestrian collision detection and avoidance behaviors in HH patients and healthy controls using a novel virtual reality (VR) walking with pedestrians, which enables natural walking behavior in an empty real-world corridor while viewing an immersive VR environment (shopping mall with colliding and other pedestrians) presented in a head-mounted display (HMD). Critically, it measure…

More Than a Score: Probing the Impact of Prompt Specificity on LLM Code Generation
Yangtian Zi, Harshitha Menon, Arjun Guha
https://arxiv.org/abs/2508.03678 https://

More Than a Score: Probing the Impact of Prompt Specificity on LLM Code Generation
State-of-the-art Large Language Models (LLMs) achieve high pass@1 on general benchmarks like HumanEval but underperform on specialized suites such as ParEval. Is this due to LLMs missing domain knowledge or insufficient prompt detail is given? To answer this, we introduce PartialOrderEval, which augments any code generation benchmark with a partial order of prompts from minimal to maximally detailed. Applying it to HumanEval and both serial and OpenMP subsets of ParEval, we measure how pass@1 s…

I'm sure this isn't much comfort to people who have lost their homes to wildfires, but it is scientifically interesting.
https://humanprogress.org/wildfire-heat-could-unexpectedly-lower-eastern-us-air-pollution/

Humanfobia – Vampire Mortuorie (B-Sides)
#byncnd

STEPWISE-CODEX-Bench: Evaluating Complex Multi-Function Comprehension and Fine-Grained Execution Reasoning
Kaiwen Yan, Yuhang Chang, Zirui Guo, Yaling Mou, Jiang Ming, Jingwei Sun
https://arxiv.org/abs/2508.05193

STEPWISE-CODEX-Bench: Evaluating Complex Multi-Function Comprehension and Fine-Grained Execution Reasoning
In recent years, large language models (LLMs) have made significant progress in code intelligence, yet systematically evaluating their code understanding and reasoning abilities remains challenging. Mainstream benchmarks such as HumanEval and MBPP primarily assess functional correctness, while reasoning benchmarks like CRUXEVAL are limited to single-function, low-complexity scenarios. As a result, advanced models achieve nearly saturated scores, limiting their discriminative power. To address t…

HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes
Keliang Li, Hongze Shen, Hao Shi, Ruibing Hou, Hong Chang, Jie Huang, Chenghao Jia, Wen Wang, Yiling Wu, Dongmei Jiang, Shiguang Shan, Xilin Chen
https://arxiv.org/abs/2508.13692

HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes
The aspiration for artificial general intelligence, fueled by the rapid progress of multimodal models, demands human-comparable performance across diverse environments. We propose HumanPCR, an evaluation suite for probing MLLMs' capacity about human-related visual contexts across three hierarchical levels: Perception, Comprehension, and Reasoning (denoted by Human-P, Human-C, and Human-R, respectively). Human-P and Human-C feature over 6,000 human-verified multiple choice questions, assessing m…

What do you think why evolution made men only learn from their own mistakes, not really from mistakes other people made? :boost_ok: #Evolution #Learning #HumanBehavior