Tootfinder

🚫 Docker Desktop unsupported, #Podman unsupported, distributions emulating Docker through Podman socket unsupported, rootless containerization solutions currently unsupported
🛠️ Built with #NodeJS and #Go

How I Built ASR for Endangered Languages with a Spoken Dictionary
Christopher Bartley, Anton Ragni
https://arxiv.org/abs/2510.04832 https://arxiv.org/pdf/2…

How I Built ASR for Endangered Languages with a Spoken Dictionary
Nearly half of the world's languages are endangered. Speech technologies such as Automatic Speech Recognition (ASR) are central to revival efforts, yet most languages remain unsupported because standard pipelines expect utterance-level supervised data. Speech data often exist for endangered languages but rarely match these formats. Manx Gaelic ($\sim$2,200 speakers), for example, has had transcribed speech since 1948, yet remains unsupported by modern systems. In this paper, we explore how litt…

no autoconf. i do not think you are truly sorry.
you will suffer for your sins

Nice thread from @… about the realities of Linux - timely in view of all those Win10 machines shortly to be unsupported.
#Linux #EndOf10

Look what an old #macOS SDK in the “Command Line Tools" tree causes on Apple Silicon:
$ clang -o ghba geh.c
In file included from geh.c:14:
In file included from /Library/Developer/CommandLineTools/SDKs/MacOSX10.14.sdk/usr/include/stdlib.h:62:
/Library/Developer/CommandLineTools/SDKs/MacOSX10.14.sdk/usr/include/sys/cdefs.h:784:2: error: Unsupported architecture
784 | <…

Enhancing the NAO: Extending Capabilities of Legacy Robots for Long-Term Research
Austin Wilson, Sahar Kapasi, Zane Greene, Alexis E. Block
https://arxiv.org/abs/2509.17760 http…

Enhancing the NAO: Extending Capabilities of Legacy Robots for Long-Term Research
Many research groups face challenges when legacy (unsupported) robotic platforms lose manufacturer support and cannot accommodate modern sensing, speech, and interaction capabilities. We present the Enhanced NAO, a revitalized version of Aldebaran's NAO robot that uses upgraded microphones, RGB-D and thermal cameras, and additional compute resources in a fully self-contained package. This system combines cloud and local models for perception and dialogue, while preserving the NAO's expressive b…

GraphMend: Code Transformations for Fixing Graph Breaks in PyTorch 2
Savini Kashmira, Jayanaka Dantanarayana, Thamirawaran Sathiyalogeswaran, Yichao Yuan, Nishil Talati, Krisztian Flautner, Lingjia Tang, Jason Mars
https://arxiv.org/abs/2509.16248

GraphMend: Code Transformations for Fixing Graph Breaks in PyTorch 2
This paper presents GraphMend, a high-level compiler that eliminates FX graph breaks in PyTorch 2 programs. Although PyTorch 2 introduced TorchDynamo and TorchInductor to enable just-in-time graph compilation, unresolved dynamic control flow and unsupported Python constructs often fragment models into multiple FX graphs. These fragments force frequent fallbacks to eager mode, incur costly CPU-to-GPU synchronizations, and reduce optimization opportunities. GraphMend addresses this limitation by …

Learning to Reason for Hallucination Span Detection
Hsuan Su, Ting-Yao Hu, Hema Swetha Koppula, Kundan Krishna, Hadi Pouransari, Cheng-Yu Hsieh, Cem Koc, Joseph Yitan Cheng, Oncel Tuzel, Raviteja Vemulapalli
https://arxiv.org/abs/2510.02173

Learning to Reason for Hallucination Span Detection
Large language models (LLMs) often generate hallucinations -- unsupported content that undermines reliability. While most prior works frame hallucination detection as a binary task, many real-world applications require identifying hallucinated spans, which is a multi-step decision making process. This naturally raises the question of whether explicit reasoning can help the complex task of detecting hallucination spans. To answer this question, we first evaluate pretrained models with and withou…