Tootfinder

Der aktuelle #UN-Bericht zeigt Fortschritte bei der Umsetzung des Global #Methane Pledge, warnt aber vor großen Lücken.
Um das Ziel einer Reduktion um 30 Prozent bis 2030 zu erreichen, müssen verfügbare Maßnahmen rasch und umfassend umgesetzt werden. Über 80 Prozent der möglichen Einsparungen sind …

Ministers urge decisive methane action as global report shows progress, warns of gaps
The Global Methane Status Report, launched today on the sidelines of COP30 in Belém, shows that while considerable progress has been made since the launch of the Global Methane Pledge in 2021, more work is required to align with the level of ambition and action needed to meet the Pledge. 

Strikes run on pizza.
Turns out they also can begin to end on them.
Several pies, in fact, arrived on North Shore Drive on the brisk Tuesday that was Oct. 18, 2022,
when the strikers first walked out of the Pittsburgh Post-Gazette newsroom
because the PG had violated federal labor law.
The workers said they would not go back to their jobs until their employer followed the rules.
They had no idea it would take three years
and become the nation’s lon…

Pittsburgh journalists vote to end country's longest strike and notify the PG they are returning to work - Pittsburgh Union Progress
The Newspaper Guild of Pittsburgh’s most momentous gathering since the formation of a strike picket line more than three years ago began last week in the manner of all big strike meetings — with the arrival of a half dozen boxes of pizza. Pepperoni, plain and a vegetarian option. Strikes run on pizza. Turns out […]

Quote post work-in-progress thread.
Boost count Quote count.
#PhanpySocialDev

Progress! Now 3 VMs to upgrade to Trixie in the next day or two, plus my office workstation and core router which are scheduled for upgrade during the maintenance outage later.
And I only have 8 VMs to switch over to the new storage setup before I can work on upgrading the hypervisor.

ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data
Zhaoyang Liu, JingJing Xie, Zichen Ding, Zehao Li, Bowen Yang, Zhenyu Wu, Xuehui Wang, Qiushi Sun, Shi Liu, Weiyun Wang, Shenglong Ye, Qingyun Li, Zeyue Tian, Gen Luo, Xiangyu Yue, Biqing Qi, Kai Chen, Bowen Zhou, Yu Qiao, Qifeng Chen, Wenhai Wang
https://arxiv.org/…

ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data
Vision-Language Models (VLMs) have enabled computer use agents (CUAs) that operate GUIs autonomously, showing great potential, yet progress is limited by the lack of large-scale, open-source computer use data and foundation models. In this work, we introduce ScaleCUA, a step toward scaling open-source CUAs. It offers a large-scale dataset spanning 6 operating systems and 3 task domains, built via a closed-loop pipeline uniting automated agents with human experts. Trained on this scaled-up data,…

A silent scenery in four acts...
(Selenium-toned[1] 4x6 salt print (still in final wash) plus previous work-in-progress stages... see alt text for details)
The picture/motif itself is one of my personal favorites and was taken 4 years ago in the Alpstein massif, when clouds were spontaneously forming around us, creating a wonderful light/scene/drama and a dear memory... now also as print which likely will/can outlast myself
[1] The tones will become more neutral once dry...…

Joel Mokyr, Philippe Aghion, and Peter Howitt win the Nobel Prize in Economics for their work on how innovation and technological progress helps economic growth (Eshe Nelson/New York Times)
https://www.nytimes.com/2025/10/13/business/nobel-prize-economics.html…

Joel Mokyr, Philippe Aghion and Peter Howitt Share Nobel in Economics
Joel Mokyr, Philippe Aghion and Peter Howitt won the prize for showing how “society must keep an eye on the factors that generate and sustain economic growth,” an award committee member said.

Omni-Captioner: Data Pipeline, Models, and Benchmark for Omni Detailed Perception
Ziyang Ma, Ruiyang Xu, Zhenghao Xing, Yunfei Chu, Yuxuan Wang, Jinzheng He, Jin Xu, Pheng-Ann Heng, Kai Yu, Junyang Lin, Eng Siong Chng, Xie Chen
https://arxiv.org/abs/2510.12720

Omni-Captioner: Data Pipeline, Models, and Benchmark for Omni Detailed Perception
Fine-grained perception of multimodal information is critical for advancing human-AI interaction. With recent progress in audio-visual technologies, Omni Language Models (OLMs), capable of processing audio and video signals in parallel, have emerged as a promising paradigm for achieving richer understanding and reasoning. However, their capacity to capture and describe fine-grained details remains limited explored. In this work, we present a systematic and comprehensive investigation of omni de…

An Empirical Study for Representations of Videos in Video Question Answering via MLLMs
Zhi Li, Yanan Wang, Hao Niu, Julio Vizcarra, Masato Taya
https://arxiv.org/abs/2510.12299 …

An Empirical Study for Representations of Videos in Video Question Answering via MLLMs
Multimodal large language models have recently achieved remarkable progress in video question answering (VideoQA) by jointly processing visual, textual, and audio information. However, it remains unclear which video representations are most effective for MLLMs, and how different modalities balance task accuracy against computational efficiency. In this work, we present a comprehensive empirical study of video representation methods for VideoQA with MLLMs. We systematically evaluate single modal…

Cowboys' defense still a work in progress under new DC Matt Eberflus, what needs to change?

https://www.cbssports.com/nfl/news/cowboys-de…

A Hybrid Agent-Based and System Dynamics Framework for Modelling Project Execution and Technology Maturity in Early-Stage R&D
R. W. S. Pessoa, M. H. N{\ae}ss, J. C. Bijos, C. M. Rebello, D. Colombo, L. Schnitman, I. B. R. Nogueira
https://arxiv.org/abs/2510.09688

A Hybrid Agent-Based and System Dynamics Framework for Modelling Project Execution and Technology Maturity in Early-Stage R&D
This paper presents a hybrid approach to predict the evolution of technological maturity in R and D projects, using the oil and gas sector as an example. Integrating System Dynamics (SD) and Agent Based Modelling (ABM) allows the proposed multi level framework to capture uncertainties in work effort, team size, and project duration, which influence technological progress. While AB SD hybrid models are established in other fields, their use in R and D remains limited. The model combines system l…

SeFEF: A Seizure Forecasting Evaluation Framework
Ana Sofia Carmo, Louren\c{c}o Abrunhosa Rodrigues, Ana Rita Peralta, Ana Fred, Carla Bentes, Hugo Pl\'acido da Silva
https://arxiv.org/abs/2510.11275

SeFEF: A Seizure Forecasting Evaluation Framework
The lack of standardization in seizure forecasting slows progress in the field and limits the clinical translation of forecasting models. In this work, we introduce a Python-based framework aimed at streamlining the development, assessment, and documentation of individualized seizure forecasting algorithms. The framework automates data labeling, cross-validation splitting, forecast post-processing, performance evaluation, and reporting. It supports various forecasting horizons and includes a …

@… same! Can't wait to get it up and running. Turns out talos.dev needs some work in progress fixes to support the pi 5 😅

Understanding Exoplanet Habitability: A Bayesian ML Framework for Predicting Atmospheric Absorption Spectra
Vasuda Trehan, Kevin H. Knuth, M. J. Way
https://arxiv.org/abs/2510.08766

Understanding Exoplanet Habitability: A Bayesian ML Framework for Predicting Atmospheric Absorption Spectra
The evolution of space technology in recent years, fueled by advancements in computing such as Artificial Intelligence (AI) and machine learning (ML), has profoundly transformed our capacity to explore the cosmos. Missions like the James Webb Space Telescope (JWST) have made information about distant objects more easily accessible, resulting in extensive amounts of valuable data. As part of this work-in-progress study, we are working to create an atmospheric absorption spectrum prediction model…

Scientists at NeurIPS, which drew a record 26,000 attendees this year, say key questions about how AI models work and how to measure them remain unresolved (Jared Perlo/NBC News)
https://www.nbcnews.com/tech/tech-news/ai-progress-surges-resea…

AI progress surges while researchers struggle to explain It
Academics, start-up founders and researchers representing industrial titans from around the globe descended on San Diego for the top gathering in AI.

Work In Progress | Australia Explained
Real stories of migrants who've made Australia their home and are building careers in vital industries...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/work-in-progress-3/

Ideal Optical Antimatter using Passive Lossy Materials under Complex Frequency Excitation
Olivia Y. Long, Peter B. Catrysse, Seunghoon Han, Shanhui Fan
https://arxiv.org/abs/2510.11796

Ideal Optical Antimatter using Passive Lossy Materials under Complex Frequency Excitation
The original concept of left-handed material has inspired the possibility of optical antimatter, where the effect of light propagation through a medium can be completely cancelled by its complementary medium. Despite recent progress in the development of negative-index metamaterials, losses continue to be a significant barrier to realizing optical antimatter. In this work, we show that passive, lossy materials can be used to realize optical antimatter when illuminated by light at a complex freq…

Ethical Considerations Around Machine Learning-Engaged Online Participatory Research - poster from Zooniverse community at #FF2025 https://zenodo.org/records/17779992

How Raiders' Chip Kelly Is Conducting Brock Bowers' Impact https://www.si.com/nfl/raiders/onsi/las-vegas-chip-kelly-conducting-brock-bowers-impact

Got this one from #springer - they're really want to fill their publications with slop. High quality articles with AI writing. No wonder people don't believe in science anymore.
F**king hate #ai #slop

Amsterdam – de Pijp
#kamafotos #35mm

We launched our product at work this week!
I don't usually post the marketingese, but I'm really proud of a lot of the work we've done and I really think our core technology is pretty cool.
Spice Labs is live. We’ve launched our Surveyor and Topographer products; available now at https://spicelabs.io.
Spice Labs maps deployment artifacts and systems with cryptographic fingerprints, anchoring them to a continuously updated ten billion node OSS database and enrichment layers to drive confident, fact-based decisions.
With comprehensive maps of your stack, replace guesswork with hard data. This enables faster decisions, reduced risk, and measurable progress across projects.
A deeper dive from our founder and CEO, David Pollak is at: https://lnkd.in/eSt8hAyX

Lessons Learned So Far From Verifying the Rust Standard Library (work-in-progress)
Alex Le Blanc, Patrick Lam
https://arxiv.org/abs/2510.01072 https://arxi…

Lessons Learned So Far From Verifying the Rust Standard Library (work-in-progress)
Although Rust primarily intends to be a safe programming language that excludes undefined behaviour, it provides its users with the escape hatch of unsafe Rust, allowing them to circumvent some of its strong compile-time checks. This additional freedom has some advantages, including potentially more efficient code, which is one of the main reasons why unsafe code is used extensively throughout Rust's standard library. However, because unsafe code also re-opens the door to undefined behaviour, A…

Strategyproof Tournament Rules for Teams with a Constant Degree of Selfishness
David Pennock, Daniel Schoepflin, Kangning Wang
https://arxiv.org/abs/2512.05235 https://arxiv.org/pdf/2512.05235 https://arxiv.org/html/2512.05235
arXiv:2512.05235v1 Announce Type: new
Abstract: We revisit the well-studied problem of designing fair and manipulation-resistant tournament rules. In this problem, we seek a mechanism that (probabilistically) identifies the winner of a tournament after observing round-robin play among $n$ teams in a league. Such a mechanism should satisfy the natural properties of monotonicity and Condorcet consistency. Moreover, from the league's perspective, the winner-determination tournament rule should be strategyproof, meaning that no team can do better by losing a game on purpose.
Past work considered settings in which each team is fully selfish, caring only about its own probability of winning, and settings in which each team is fully selfless, caring only about the total winning probability of itself and the team to which it deliberately loses. More recently, researchers considered a mixture of these two settings with a parameter $\lambda$. Intermediate selfishness $\lambda$ means that a team will not lose on purpose unless its pair gains at least $\lambda s$ winning probability, where $s$ is the individual team's sacrifice from its own winning probability. All of the dozens of previously known tournament rules require $\lambda = \Omega(n)$ to be strategyproof, and it has been an open problem to find such a rule with the smallest $\lambda$.
In this work, we make significant progress by designing a tournament rule that is strategyproof with $\lambda = 11$. Along the way, we propose a new notion of multiplicative pairwise non-manipulability that ensures that two teams cannot manipulate the outcome of a game to increase the sum of their winning probabilities by more than a multiplicative factor $\delta$ and provide a rule which is multiplicatively pairwise non-manipulable for $\delta = 3.5$.
toXiv_bot_toot

I've been working on a bit of a larger project. It is still very much a work in progress. It's an attempt to combine blog and mastodon posts with other things I've written in the past, along with some original analysis, into a zine. I'm probably about 2/3 of the way through.
It's primarily focused on political theory and critique, which, I think, deviates a bit from how a lot of other folks view the world. It's pretty explicitly anarchist, though I don't think I've actually put the word "anarchism" or referenced the ideology anywhere so explicitly.
I'd love feedback (especially around editing and flow) if anyone would be willing to put eyes on it and tell me what they think:
https://anarchoccultism.org/building-zion/

OpenGL GPU-Based Rowhammer Attack (Work in Progress)
Antoine Plin, Fr\'ed\'eric Fauberteau, Nga Nguyen
https://arxiv.org/abs/2509.19959 https://arx…

OpenGL GPU-Based Rowhammer Attack (Work in Progress)
Rowhammer attacks have emerged as a significant threat to modern DRAM-based memory systems, leveraging frequent memory accesses to induce bit flips in adjacent memory cells. This work-in-progress paper presents an adaptive, many-sided Rowhammer attack utilizing GPU compute shaders to systematically achieve high-frequency memory access patterns. Our approach employs statistical distributions to optimize row targeting and avoid current mitigations. The methodology involves initializing memory wit…

OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
Hongpei Li, Han Zhang, Huikang Liu, Dongdong Ge, Yinyu Ye
https://arxiv.org/abs/2510.05186 https:…

OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
Pipeline parallelism (PP) has become a standard technique for scaling large language model (LLM) training across multiple devices. However, despite recent progress in reducing memory consumption through activation offloading, existing approaches remain largely heuristic and coarse-grained, often overlooking the fine-grained trade-offs between memory, computation, and scheduling latency. In this work, we revisit the pipeline scheduling problem from a principled optimization perspective. We obser…

EigenScore: OOD Detection using Covariance in Diffusion Models
Shirin Shoushtari, Yi Wang, Xiao Shi, M. Salman Asif, Ulugbek S. Kamilov
https://arxiv.org/abs/2510.07206 https://…

EigenScore: OOD Detection using Covariance in Diffusion Models
Out-of-distribution (OOD) detection is critical for the safe deployment of machine learning systems in safety-sensitive domains. Diffusion models have recently emerged as powerful generative models, capable of capturing complex data distributions through iterative denoising. Building on this progress, recent work has explored their potential for OOD detection. We propose EigenScore, a new OOD detection method that leverages the eigenvalue spectrum of the posterior covariance induced by a diffus…

MaP: A Unified Framework for Reliable Evaluation of Pre-training Dynamics
Jiapeng Wang, Changxin Tian, Kunlong Chen, Ziqi Liu, Jiaxin Mao, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou
https://arxiv.org/abs/2510.09295

MaP: A Unified Framework for Reliable Evaluation of Pre-training Dynamics
Reliable evaluation is fundamental to the progress of Large Language Models (LLMs), yet the evaluation process during pre-training is plagued by significant instability that obscures true learning dynamics. In this work, we systematically diagnose this instability, attributing it to two distinct sources: \textit{Parameter Instability} from training stochasticity and \textit{Evaluation Instability} from noisy measurement protocols. To counteract both sources of noise, we introduce \textbf{MaP}, …

It's gonna be interesting to see how Ed Zitron's popularity will develop after that Wired article.
Most people will probably be pissed off about him doing PR for AI companies but I think the more relevant part is that his analysis is kinda ... shallow? Like he fully lives in "the computer is the machine that generates social progress" camp. Which ... doesn't hold too much water.
Which doesn't mean that he's not doing some good work digging through t…

Towards Developing Standards and Guidelines for Robot Grasping and Manipulation Pipelines in the COMPARE Ecosystem
Huajing Zhao, Brian Flynn, Adam Norton, Holly Yanco
https://arxiv.org/abs/2509.22801

Towards Developing Standards and Guidelines for Robot Grasping and Manipulation Pipelines in the COMPARE Ecosystem
The COMPARE Ecosystem aims to improve the compatibility and benchmarking of open-source products for robot manipulation through a series of activities. One such activity is the development of standards and guidelines to specify modularization practices at the component-level for individual modules (e.g., perception, grasp planning, motion planning) and integrations of components that form robot manipulation capabilities at the pipeline-level. This paper briefly reviews our work-in-progress to d…

shots fired:
> it’s abundantly clear that the talented folks who used to work on the product have moved on to bigger and better things, with the remaining rookies eager to inflict some kind of bloated, buggy JavaScript framework on us in the name of progress. Stuff that used to be snappy is now sluggish and often entirely broken.
…

Observables in Motion: A guide to simulating classical and quantum dynamics
Denys I. Bondar, Gerard McCaul, Andrii Sotnikov
https://arxiv.org/abs/2509.20403 https://

Observables in Motion: A guide to simulating classical and quantum dynamics
We present a pedagogical work-in-progress. This textbook aims to introduce Hilbert space representations for quantum and classical dynamics, outlining the mathematical foundations, practical guidance, and Python implementation of dynamical simulations. Beginning with a historical survey, the book systematically develops the mathematical foundations, kinematic descriptions, and formal evolution theory needed to understand both classical and quantum systems. It then provides practical guidance fo…

Preview of a new 🌈 node joining the cluster, once talos.dev fully supports the #RaspberryPi 5. It's a work in progress, and there are temporary options: https://github.com/siderolabs/sbc-rasp

There's no such a thing as coincidence.
There you have EuroBSDCon.
And FreeBSD 15-alpha3 is available.
And then your wifi card does work, showing lots of progress and hard work on the devs side.
And Plasma 6.4.5 has been packaged, so it installs straightaway.
Time for me to update my howto for Plasma 6 Wayland on FreeBSD this weekend!
Cheers and thanks to all in Zagreb 🍻
cc @…

MPMAvatar: Learning 3D Gaussian Avatars with Accurate and Robust Physics-Based Dynamics
Changmin Lee, Jihyun Lee, Tae-Kyun Kim
https://arxiv.org/abs/2510.01619 https://

MPMAvatar: Learning 3D Gaussian Avatars with Accurate and Robust Physics-Based Dynamics
While there has been significant progress in the field of 3D avatar creation from visual observations, modeling physically plausible dynamics of humans with loose garments remains a challenging problem. Although a few existing works address this problem by leveraging physical simulation, they suffer from limited accuracy or robustness to novel animation inputs. In this work, we present MPMAvatar, a framework for creating 3D human avatars from multi-view videos that supports highly realistic, ro…

Compose Yourself: Average-Velocity Flow Matching for One-Step Speech Enhancement
Gang Yang, Yue Lei, Wenxin Tai, Jin Wu, Jia Chen, Ting Zhong, Fan Zhou
https://arxiv.org/abs/2509.15952

Compose Yourself: Average-Velocity Flow Matching for One-Step Speech Enhancement
Diffusion and flow matching (FM) models have achieved remarkable progress in speech enhancement (SE), yet their dependence on multi-step generation is computationally expensive and vulnerable to discretization errors. Recent advances in one-step generative modeling, particularly MeanFlow, provide a promising alternative by reformulating dynamics through average velocity fields. In this work, we present COSE, a one-step FM framework tailored for SE. To address the high training overhead of Jacob…

South Korea confirms that a fire at National Information Resources Service's data center, housing 647 government IT systems, directly damaged 96 of them (Lee Jung-joo/The Korea Herald)
https://www.koreaherald.com/article/10585032

Govt. races to restore services after data center blaze; 96 systems confirmed damaged - The Korea Herald
The Ministry of Interior and Safety said Sunday that recovery work is currently in progress at the government-run National Information Resources Service in Daej

Probing a theoretical framework for a Photonic Extreme Learning Machine
Vicente Rocha, Duarte Silva, Felipe C. Moreira, Catarina S. Monteiro, Tiago D. Ferreira, Nuno A. Silva
https://arxiv.org/abs/2510.02918

Probing a theoretical framework for a Photonic Extreme Learning Machine
The development of computing paradigms alternative to von Neumann architectures has recently fueled significant progress in novel all-optical processing solutions. In this work, we investigate how the coherence properties can be exploited for computing by expanding information onto a higher-dimensional space in the photonic extreme learning machine framework. A theoretical framework is provided based on the transmission matrix formalism, mapping the input plane onto the output camera plane, res…

#WritersCoffeeClub
25. How many works do you have in progress at a time?
26. How does your heritage show itself in your work?
27. How do you support your fellow writers?
---
25. At most two to three. Usually no more than one. Not counting background ones where I accumulate snippets without actively writing.
26. I don't like the word much. But I believe my cu…

Jerry Jones gives 'bottom line' message on improving Cowboys defense https://www.sportingnews.com/us/nfl/dallas-cowboys/news/jerry-jones-gives-bottom-line-message-improving-cowboys-defense/1702…

Towards a user-centric HPC-QC environment
Aleksander Wennersteen, Matthieu Moreau, Aurelien Nober, Mourad Beji
https://arxiv.org/abs/2509.20525 https://arx…

Towards a user-centric HPC-QC environment
Robust execution environments are important for addressing key challenges in quantum computing, such as application development, portability, and reproducibility, and help unlock the development of modular quantum programs, driving forward hybrid quantum workflows. In this work, we show progress towards a basic, but portable, runtime environment for developing and executing hybrid quantum-classical programs running in High Performance Computing (HPC) environments enhanced with Quantum Processin…

Syntax-Guided Diffusion Language Models with User-Integrated Personalization
Ruqian Zhang, Yijiao Zhang, Juan Shen, Zhongyi Zhu, Annie Qu
https://arxiv.org/abs/2510.01028 https:…

Syntax-Guided Diffusion Language Models with User-Integrated Personalization
Large language models have made revolutionary progress in generating human-like text, yet their outputs often tend to be generic, exhibiting insufficient structural diversity, which limits personalized expression. Recent advances in diffusion models have opened new opportunities for improving language generation beyond the limitations of autoregressive paradigms. In this work, we propose a syntax-guided diffusion language model that integrates structural supervision and personalized conditionin…

Efficient $\varepsilon$-approximate minimum-entropy couplings
Spencer Compton
https://arxiv.org/abs/2509.19598 https://arxiv.org/pdf/2509.19598

Efficient $\varepsilon$-approximate minimum-entropy couplings
Given $m \ge 2$ discrete probability distributions over $n$ states each, the minimum-entropy coupling is the minimum-entropy joint distribution whose marginals are the same as the input distributions. Computing the minimum-entropy coupling is NP-hard, but there has been significant progress in designing approximation algorithms; prior to this work, the best known polynomial-time algorithms attain guarantees of the form $H(\operatorname{ALG}) \le H(\operatorname{OPT}) + c$, where $c \approx 0.53…

FreezeVLA: Action-Freezing Attacks against Vision-Language-Action Models
Xin Wang, Jie Li, Zejia Weng, Yixu Wang, Yifeng Gao, Tianyu Pang, Chao Du, Yan Teng, Yingchun Wang, Zuxuan Wu, Xingjun Ma, Yu-Gang Jiang
https://arxiv.org/abs/2509.19870

FreezeVLA: Action-Freezing Attacks against Vision-Language-Action Models
Vision-Language-Action (VLA) models are driving rapid progress in robotics by enabling agents to interpret multimodal inputs and execute complex, long-horizon tasks. However, their safety and robustness against adversarial attacks remain largely underexplored. In this work, we identify and formalize a critical adversarial vulnerability in which adversarial images can "freeze" VLA models and cause them to ignore subsequent instructions. This threat effectively disconnects the robot's digital min…

ARIONet: An Advanced Self-supervised Contrastive Representation Network for Birdsong Classification and Future Frame Prediction
Md. Abdur Rahman, Selvarajah Thuseethan, Kheng Cher Yeo, Reem E. Mohamed, Sami Azam
https://arxiv.org/abs/2510.00522

ARIONet: An Advanced Self-supervised Contrastive Representation Network for Birdsong Classification and Future Frame Prediction
Automated birdsong classification is essential for advancing ecological monitoring and biodiversity studies. Despite recent progress, existing methods often depend heavily on labeled data, use limited feature representations, and overlook temporal dynamics essential for accurate species identification. In this work, we propose a self-supervised contrastive network, ARIONet (Acoustic Representation for Interframe Objective Network), that jointly optimizes contrastive classification and future fr…

EuroSpeech: A Multilingual Speech Corpus
Samuel Pfisterer, Florian Gr\"otschla, Luca A. Lanzend\"orfer, Florian Yan, Roger Wattenhofer
https://arxiv.org/abs/2510.00514

EuroSpeech: A Multilingual Speech Corpus
Recent progress in speech processing has highlighted that high-quality performance across languages requires substantial training data for each individual language. While existing multilingual datasets cover many languages, they often contain insufficient data for most languages. Thus, trained models perform poorly on the majority of the supported languages. Our work addresses this challenge by introducing a scalable pipeline for constructing speech datasets from parliamentary recordings. The p…

Raiders’ Ashton Jeanty Speaks Up on Rookie Season https://www.si.com/nfl/raiders/onsi/las-vegas-ashton-jeanty-speaks-up-rookie-season

UniSS: Unified Expressive Speech-to-Speech Translation with Your Voice
Sitong Cheng, Weizhen Bian, Xinsheng Wang, Ruibin Yuan, Jianyi Chen, Shunshun Yin, Yike Guo, Wei Xue
https://arxiv.org/abs/2509.21144

UniSS: Unified Expressive Speech-to-Speech Translation with Your Voice
The ultimate goal of expressive speech-to-speech translation (S2ST) is to accurately translate spoken content while preserving the speaker identity and emotional style. However, progress in this field is largely hindered by three key challenges: the scarcity of paired speech data that retains expressive styles, the complexity of multi-stage processing pipelines, and the limited transfer of translation capabilities from large language models (LLMs). In this work, we address these challenges by i…

Monolithic Expandable-FOV Metalens Enabled by Radially Gradient-Tilted Meta-Atoms
Feiyang Zhang, Guoxia Han, Yihan Tian, Yanbin Ma, Xianghua Yu, Xiaolong Liu
https://arxiv.org/abs/2509.17524

Monolithic Expandable-FOV Metalens Enabled by Radially Gradient-Tilted Meta-Atoms
Metalens, as the most promising and applicable emerging optical device, has long been constrained by the limited field of view (FOV). Recent studies employing phase engineering or multi-layer strategies have made some progress, but they all rely on upright meta-atoms. This leads us to consider whether tilted meta-atoms could represent a promising yet underexplored approach for enhancing the field of view? In this work, we introduce the control of the tilt angle of meta-atoms as a new degree of …

Interpretable Audio Editing Evaluation via Chain-of-Thought Difference-Commonality Reasoning with Multimodal LLMs
Yuhang Jia, Xu Zhang, Yang Chen, Hui Wang, Enzhi Wang, Yong Qin
https://arxiv.org/abs/2509.16975

Interpretable Audio Editing Evaluation via Chain-of-Thought Difference-Commonality Reasoning with Multimodal LLMs
Automatic mean opinion score (MOS) prediction provides a more perceptual alternative to objective metrics, offering deeper insights into the evaluated models. With the rapid progress of multimodal large language models (MLLMs), their enhanced perceptual and reasoning abilities enable more comprehensive and interpretable audio quality assessment. In this work, we tackle the challenging task of audio editing evaluation and propose the first natural language-based automated evaluation framework bu…