Tootfinder

Anti-Trump former Republicans have a multimillion-dollar plan to save House Democrats (Andrew Howard/Politico)
https://www.politico.com/news/2025/12/08/anti-trump-former-republicans-have-a-multimillion-dollar-plan-to-save-house-democrats-00680114
http://www.memeorandum.com/251208/p53#a251208p53

M3Retrieve: Benchmarking Multimodal Retrieval for Medicine
Arkadeep Acharya, Akash Ghosh, Pradeepika Verma, Kitsuchart Pasupa, Sriparna Saha, Priti Singh
https://arxiv.org/abs/2510.06888

M3Retrieve: Benchmarking Multimodal Retrieval for Medicine
With the increasing use of RetrievalAugmented Generation (RAG), strong retrieval models have become more important than ever. In healthcare, multimodal retrieval models that combine information from both text and images offer major advantages for many downstream tasks such as question answering, cross-modal retrieval, and multimodal summarization, since medical data often includes both formats. However, there is currently no standard benchmark to evaluate how well these models perform in medica…

Dust, sand and wind drive slope streaks on #Mars: https://www.nature.com/articles/s41467-025-65522-4 -> Swoosh! https://www.esa.int/ESA_Multimedia/Images/2025/11/Swoosh

Engineering Rogue Waves via Multimode Interactions in Integrated Waveguides
G\"uls\"um Yaren Durdu, Azka Maula Iskandar Muda, U\u{g}ur Te\u{g}in
https://arxiv.org/abs/2510.07082

Engineering Rogue Waves via Multimode Interactions in Integrated Waveguides
We explore rogue wave formation in multimode silicon nitride (Si$_3$N$_4$) waveguides with multimode nonlinear Schrödinger equation-based simulations. Pure fundamental-mode excitation produces smooth propagation without extreme events, whereas higher-order modes or multimode superpositions yield heavy-tailed statistics with bursts exceeding the $8σ$ threshold. These results reveal that rogue wave generation in integrated waveguides is controlled not only by material properties such as nonline…

Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Oz
Frederic Gmeiner, Kenneth Holstein, Nikolas Martelaro
https://arxiv.org/abs/2510.06872

Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Oz
Recent advancements in multimodal generative AI (GenAI) enable the creation of personal context-aware real-time agents that, for example, can augment user workflows by following their on-screen activities and providing contextual assistance. However, prototyping such experiences is challenging, especially when supporting people with domain-specific tasks using real-time inputs such as speech and screen recordings. While prototyping an LLM-based proactive support agent system, we found that exis…

Sir a second antifa furry plane hit the Trump tower

Trump Waives Southwest Airlines Fine For Holiday Meltdown
https://www.levernews.com/trump-waives-southwest-airlines-fine-for-holiday-meltdown/

DreamOmni2: Multimodal Instruction-based Editing and Generation
Bin Xia, Bohao Peng, Yuechen Zhang, Junjia Huang, Jiyang Liu, Jingyao Li, Haoru Tan, Sitong Wu, Chengyao Wang, Yitong Wang, Xinglong Wu, Bei Yu, Jiaya Jia
https://arxiv.org/abs/2510.06679

DreamOmni2: Multimodal Instruction-based Editing and Generation
Recent advancements in instruction-based image editing and subject-driven generation have garnered significant attention, yet both tasks still face limitations in meeting practical user needs. Instruction-based editing relies solely on language instructions, which often fail to capture specific editing details, making reference images necessary. Meanwhile, subject-driven generation is limited to combining concrete objects or people, overlooking broader, abstract concepts. To address these chall…

ToolMem: Enhancing Multimodal Agents with Learnable Tool Capability Memory
Yunzhong Xiao, Yangmin Li, Hewei Wang, Yunlong Tang, Zora Zhiruo Wang
https://arxiv.org/abs/2510.06664

ToolMem: Enhancing Multimodal Agents with Learnable Tool Capability Memory
Agents utilizing tools powered by large language models (LLMs) or vision-language models (VLMs) have demonstrated remarkable progress in diverse tasks across text and visual modalities. Unlike traditional tools such as calculators, which give deterministic outputs, neural tools perform uncertainly across task scenarios. While different tools for a task may excel in varied scenarios, existing agents typically rely on fixed tools, thus limiting the flexibility in selecting the most suitable tool …