Tootfinder

Multilingual Multimodal Software Developer for Code Generation
Linzheng Chai, Jian Yang, Shukai Liu, Wei Zhang, Liran Wang, Ke Jin, Tao Sun, Congnan Liu, Chenchen Zhang, Hualei Zhu, Jiaheng Liu, Xianjie Wu, Ge Zhang, Tianyu Liu, Zhoujun Li
https://arxiv.org/abs/2507.08719

Multilingual Multimodal Software Developer for Code Generation
The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and flowcharts used in real-world software development. To bridge this gap, we introduce MM-Coder, a Multilingual Multimodal software developer. MM-Coder integrates visual design inputs-Unified Modeling Language (UML) diagrams and flowcharts (termed Visual Workflow)-with textual instructions to enhance code generation ac…

Laser Guided Microbubble Lithography for Multilayer Biophotonic Heterostructures
Anand Dev Ranjan, Suyash Narayan Amzare, Subhrokoli Ghosh, Ayan Banerjee
https://arxiv.org/abs/2506.10320

Laser Guided Microbubble Lithography for Multilayer Biophotonic Heterostructures
The fabrication of multilayered heterostructures is essential for advancing microelectronic and biosensing technologies. Conventional top-down manufacturing techniques are often cost-prohibitive and unsuitable for biomedical applications. Here, we present a bottom-up fabrication method, termed microbubble lithography, which enables the in situ construction of multilayered microstructures through layer-by-layer self-assembly. This technique allows diverse materials to be integrated into coherent…

The AI Language Proficiency Monitor -- Tracking the Progress of LLMs on Multilingual Benchmarks
David Pomerenke, Jonas Nothnagel, Simon Ostermann
https://arxiv.org/abs/2507.08538 …

The AI Language Proficiency Monitor -- Tracking the Progress of LLMs on Multilingual Benchmarks
To ensure equitable access to the benefits of large language models (LLMs), it is essential to evaluate their capabilities across the world's languages. We introduce the AI Language Proficiency Monitor, a comprehensive multilingual benchmark that systematically assesses LLM performance across up to 200 languages, with a particular focus on low-resource languages. Our benchmark aggregates diverse tasks including translation, question answering, math, and reasoning, using datasets such as FLORES+…

In mildly startling news: Venom - The Last Dance was *not awful.* Decent tea-time film, a solid 6/10.

Tip-Based Proximity Ferroelectric Switching and Piezoelectric Response in Wurtzite Multilayers
Eugene A. Eliseev, Anna N. Morozovska, Sergei V. Kalinin, Long-Qing Chen, Venkatraman Gopalan
https://arxiv.org/abs/2506.09196

Tip-Based Proximity Ferroelectric Switching and Piezoelectric Response in Wurtzite Multilayers
Proximity ferroelectricity is a novel paradigm for inducing ferroelectricity, where a non-ferroelectric polar material, which is unswitchable with an external field below the dielectric breakdown field, becomes a practically switchable ferroelectric in direct contact with a thin switchable ferroelectric layer. Here, we develop a Landau-Ginzburg-Devonshire approach to study the proximity effect of local piezoelectric response and polarization reversal in wurtzite ferroelectric multilayers under …

Temperature gradient-driven motion of magnetic domains in a magnetic metal multilayer by entropic forces
Lin Huang, Joseph Barker, Lekshmi Kailas, Soumyarup Hait, Simon D. Connell, Gavin Burnell, Christopher H. Marrows
https://arxiv.org/abs/2506.09628

Temperature gradient-driven motion of magnetic domains in a magnetic metal multilayer by entropic forces
We studied the displacement of magnetic domains under temperature gradients in perpendicularly magnetized Ta/[Pt/Co$_{68}$B$_{32}$/Ir]$_{\times 10}$/Pt multilayer tracks with microfabricated Pt heaters/thermometers by magnetic force microscopy (MFM). Subtracting out the effects of the Oersted field from the heating current reveals the pure temperature gradient-driven motion, which is always towards the heater. The higher the thermal gradient along the track (owing to proximity to the heater or …

Beyond N-Grams: Rethinking Evaluation Metrics and Strategies for Multilingual Abstractive Summarization
Itai Mondshine, Tzuf Paz-Argaman, Reut Tsarfaty
https://arxiv.org/abs/2507.08342

Beyond N-Grams: Rethinking Evaluation Metrics and Strategies for Multilingual Abstractive Summarization
Automatic n-gram based metrics such as ROUGE are widely used for evaluating generative tasks such as summarization. While these metrics are considered indicative (even if imperfect) of human evaluation for English, their suitability for other languages remains unclear. To address this, we systematically assess evaluation metrics for generation both n-gram-based and neural based to evaluate their effectiveness across languages and tasks. Specifically, we design a large-scale evaluation suite acr…

ILT-Iterative LoRA Training through Focus-Feedback-Fix for Multilingual Speech Recognition
Qingliang Meng, Hao Wu, Wei Liang, Wei Xu, Qing Zhao
https://arxiv.org/abs/2507.08477

ILT-Iterative LoRA Training through Focus-Feedback-Fix for Multilingual Speech Recognition
The deep integration of large language models and automatic speech recognition systems has become a promising research direction with high practical value. To address the overfitting issue commonly observed in Low-Rank Adaptation (LoRA) during the supervised fine-tuning (SFT) stage, this work proposes an innovative training paradigm Iterative LoRA Training (ILT) in combination with an Iterative Pseudo Labeling strategy, effectively enhancing the theoretical upper bound of model performance. Bas…

Checklist Engineering Empowers Multilingual LLM Judges
Mohammad Ghiasvand Mohammadkhani, Hamid Beigy
https://arxiv.org/abs/2507.06774 https://

Checklist Engineering Empowers Multilingual LLM Judges
Automated text evaluation has long been a central issue in Natural Language Processing (NLP). Recently, the field has shifted toward using Large Language Models (LLMs) as evaluators-a trend known as the LLM-as-a-Judge paradigm. While promising and easily adaptable across tasks, this approach has seen limited exploration in multilingual contexts. Existing multilingual studies often rely on proprietary models or require extensive training data for fine-tuning, raising concerns about cost, time, a…

KELPS: A Framework for Verified Multi-Language Autoformalization via Semantic-Syntactic Alignment
Jiyao Zhang, Chengli Zhong, Hui Xu, Qige Li, Yi Zhou
https://arxiv.org/abs/2507.08665

KELPS: A Framework for Verified Multi-Language Autoformalization via Semantic-Syntactic Alignment
Modern large language models (LLMs) show promising progress in formalizing informal mathematics into machine-verifiable theorems. However, these methods still face bottlenecks due to the limited quantity and quality of multilingual parallel corpora. In this paper, we propose a novel neuro-symbolic framework KELPS (Knowledge-Equation based Logical Processing System) to address these problems. KELPS is an iterative framework for translating, synthesizing, and filtering informal data into multiple…