Tootfinder

It's all very well to suggest people suddenly switch from the jobs that AI has taken, but who's going to hire all those manual workers?
There's no money any more... the very few have it all.
🤔

Several Hotels and Resorts in the Philippines Commit to Making Their Menus 30% Plant-Based https://vegconomist.com/gastronomy-food-service/food-service/hotels-resorts-the-philippines-commit-making-menus-30-plant-based/…

Several Hotels and Resorts in the Philippines Commit to Making Their Menus 30% Plant-Based - vegconomist - the vegan business magazine
According to Inside Asian Gaming, Winford Resort & Casino Manila is the first gaming complex in the Philippines to commit to making 30% of its menu plant-based.

Pretty sure my mom gets that “flying-an-airplane-without-a-manual” feeling whenever she walks in and catches sight of my anarchist flag waving next to the rainbow, trans, and neurodiversity pride flags.
#Autism #ActuallyAutistic

Interpretable Decision-Making for End-to-End Autonomous Driving
Mona Mirzaie, Bodo Rosenhahn
https://arxiv.org/abs/2508.18898 https://arxiv.org/pdf/2508.18…

Interpretable Decision-Making for End-to-End Autonomous Driving
Trustworthy AI is mandatory for the broad deployment of autonomous vehicles. Although end-to-end approaches derive control commands directly from raw data, interpreting these decisions remains challenging, especially in complex urban scenarios. This is mainly attributed to very deep neural networks with non-linear decision boundaries, making it challenging to grasp the logic behind AI-driven decisions. This paper presents a method to enhance interpretability while optimizing control commands in…

ILRe: Intermediate Layer Retrieval for Context Compression in Causal Language Models
Manlai Liang, Mandi Liu, Jiangzhou Ji, Huaijun Li, Haobo Yang, Yaohan He, Jinlong Li
https://arxiv.org/abs/2508.17892

ILRe: Intermediate Layer Retrieval for Context Compression in Causal Language Models
Large Language Models (LLMs) have demonstrated success across many benchmarks. However, they still exhibit limitations in long-context scenarios, primarily due to their short effective context length, quadratic computational complexity, and high memory overhead when processing lengthy inputs. To mitigate these issues, we introduce a novel context compression pipeline, called Intermediate Layer Retrieval (ILRe), which determines one intermediate decoder layer offline, encodes context by streamin…

$ git soda pop
update: https://git-man-page-generator.lokaltog.net/#c29kYSQkcG9w

All-Dielectric Metasurface with a Two-Dimensional Locally Flat Photonic Band
Minho Choi, Christopher Munley, Arnab Manna, Johannes Fr\"och, Arthur Barnard, Arka Majumdar
https://arxiv.org/abs/2506.20871

All-Dielectric Metasurface with a Two-Dimensional Locally Flat Photonic Band
Photonic flatbands offer promising light-matter interaction due to their unique slow-light nature. In recent years, flatbands have also attracted significant interest in optical engineering because of their angle-insensitive resonant characteristics. However, most photonic flatbands demonstrated to date occur only in one dimension and for a specific polarization, limiting their applicability. To date, no studies have reported the dispersionless behavior of flatbands under arbitrary two-dimensio…

Hiding behind a curtain of dust: Gas and dust properties of an ultra-luminous strongly-lensed z = 3.75 galaxy behind the Milky Way disk
Bel\'en Alcalde Pampliega, Kevin C. Harrington, Aristeidis Amvrosiadis, Manuel Aravena, Min S. Yun, Hugo Messias, Antonio Hern\'an-Caballero, Leindert Boogaard, Axel Wei{\ss}, Benjamin Beauchesne, Alejandro Santamar\'ia-Miranda, Monica Ivette Rodriguez, Eric Jim\'enez-Andrade, Manuel Solimano, James Lowenthal, Pascale Hibon, Patrick Kam…

Hiding behind a curtain of dust: Gas and dust properties of an ultra-luminous strongly-lensed z = 3.75 galaxy behind the Milky Way disk
We present a detailed analysis of J154506, a strongly lensed submillimeter galaxy (SMG) behind the Lupus-I molecular cloud, and characterization of its physical properties. Using a combination of archival and new data (including sub-arcsecond resolution ($\sim0.75$) ALMA observations, VLT/MUSE and FORS2 optical data, as well as spectral scans from the ACA and the LMT) we identify two high-significance (SNR>5) emission lines at 97.0 and 145.5 GHz, corresponding to CO(4-3) and CO(6-5), respective…

UniC-RAG: Universal Knowledge Corruption Attacks to Retrieval-Augmented Generation
Runpeng Geng, Yanting Wang, Ying Chen, Jinyuan Jia
https://arxiv.org/abs/2508.18652 https://…

UniC-RAG: Universal Knowledge Corruption Attacks to Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) systems are widely deployed in real-world applications in diverse domains such as finance, healthcare, and cybersecurity. However, many studies showed that they are vulnerable to knowledge corruption attacks, where an attacker can inject adversarial texts into the knowledge database of a RAG system to induce the LLM to generate attacker-desired outputs. Existing studies mainly focus on attacking specific queries or queries with similar topics (or keywords). …

SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning
Si-Woo Kim, MinJu Jeon, Ye-Chan Kim, Soeun Lee, Taewhan Kim, Dong-Jin Kim
https://arxiv.org/abs/2507.18616

SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning
Zero-shot Image Captioning (ZIC) increasingly utilizes synthetic datasets generated by text-to-image (T2I) models to mitigate the need for costly manual annotation. However, these T2I models often produce images that exhibit semantic misalignments with their corresponding input captions (e.g., missing objects, incorrect attributes), resulting in noisy synthetic image-caption pairs that can hinder model training. Existing dataset pruning techniques are largely designed for removing noisy text in…