Tootfinder

Supreme Court to hear Alabama appeal in push to execute intellectually disabled man | The Independent
https://www.independent.co.uk/news/world/americas/supreme-court-execute-intellectually-disabled-joseph-clifton-smith-b2765542.html

Reading Command output line by line
Sometimes, you want to execute a system command from within a Go app and process it's output line-by-line in a streaming fashion.
https://www.yellowduck.be/posts/reading-command-output-line-by-line/

"Meanwhile, others see signs of success. That code (actually from 2006) is still there because, well, it is still there, because its authors did not get distracted by the shiny shiny and get bogged down in another rewrite, because as manufacturers and markets came and went, the Java runtime was still there, and the bytecode could still execute."

Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
Ke Ma, Junfei Xie
https://arxiv.org/abs/2506.04456 https://

Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
Vehicle edge computing (VEC) brings abundant computing resources close to vehicles by deploying them at roadside units (RSUs) or base stations, thereby enabling diverse computation-intensive and delay sensitive applications. Existing task offloading strategies are often computationally expensive to execute or generate suboptimal solutions. In this paper, we propose a novel learning-based approach, Knowledge-guided Attention-inspired Task Offloading (KATO), designed to efficiently offload tasks …

I've just found out that the nano text editor can sort lines by pressing Ctrl-T (execute any command on marked lines) and then entering "| sort" (like in a shell pipe).
https://unix.stackexchange.com/a/717925

from my link log —
Implement your programming language twice.
https://futhark-lang.org/blog/2025-05-07-implement-your-language-twice.html
saved 2025-05-08

Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody
David Sasu, Kweku Andoh Yamoah, Benedict Quartey, Natalie Schluter
https://arxiv.org/abs/2506.02057

Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody
Enabling robots to accurately interpret and execute spoken language instructions is essential for effective human-robot collaboration. Traditional methods rely on speech recognition to transcribe speech into text, often discarding crucial prosodic cues needed for disambiguating intent. We propose a novel approach that directly leverages speech prosody to infer and resolve instruction intent. Predicted intents are integrated into large language models via in-context learning to disambiguate and …

This https://arxiv.org/abs/2505.16764 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Can a domain-specific language improve program structure comprehension of data pipelines? A mixed-methods study
In many application domains, domain-specific languages can allow domain experts to contribute to collaborative projects more correctly and efficiently. To do so, they must be able to understand program structure from reading existing source code. With high-quality data becoming an increasingly important resource, the creation of data pipelines is an important application domain for domain-specific languages. We execute a mixed-method study consisting of a controlled experiment and a follow-up…

Improving LLM Agents with Reinforcement Learning on Cryptographic CTF Challenges
Lajos Muzsai, David Imolai, Andr\'as Luk\'acs
https://arxiv.org/abs/2506.02048

Improving LLM Agents with Reinforcement Learning on Cryptographic CTF Challenges
Large Language Models (LLMs) still struggle with the structured reasoning and tool-assisted computation needed for problem solving in cybersecurity applications. In this work, we introduce "random-crypto", a cryptographic Capture-the-Flag (CTF) challenge generator framework that we use to fine-tune a tool-augmented Llama-3.1-8B with Guided Reinforcement Prompt Optimisation (GRPO), allowing the agent to iteratively write and execute Python inside an isolated REPL. GRPO yields a +53% absolute jum…

This https://arxiv.org/abs/2505.23073 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

DX100: A Programmable Data Access Accelerator for Indirection
Indirect memory accesses frequently appear in applications where memory bandwidth is a critical bottleneck. Prior indirect memory access proposals, such as indirect prefetchers, runahead execution, fetchers, and decoupled access/execute architectures, primarily focus on improving memory access latency by loading data ahead of computation but still rely on the DRAM controllers to reorder memory requests and enhance memory bandwidth utilization. DRAM controllers have limited visibility to future …

"What Stroustrup wanted was apparently what a lot of people wanted: a language that provided OOP features, such as those offered by Smalltalk, but compiled into binaries that would execute as fast as an executable written in C.
The solution Stroustrup adopted was not to adopt the Smalltalk model, but instead to take inspiration from fellow Scandinavians and to bolt ideas borrowed from Simula into C."

from my link log —
Decomposing transactional systems.
https://transactional.blog/blog/2025-decomposing-transactional-systems
saved 2025-04-18

This https://arxiv.org/abs/2505.14314 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

Low-Cost FlashAttention with Fused Exponential and Multiplication Hardware Operators
Attention mechanisms, particularly within Transformer architectures and large language models (LLMs), have revolutionized sequence modeling in machine learning and artificial intelligence applications. To compute attention for increasingly long sequences, specialized accelerators have been proposed to execute key attention steps directly in hardware. Among the various recently proposed architectures, those based on variants of the FlashAttention algorithm, originally designed for GPUs, stand ou…

AgentAlign: Navigating Safety Alignment in the Shift from Informative to Agentic Large Language Models
Jinchuan Zhang, Lu Yin, Yan Zhou, Songlin Hu
https://arxiv.org/abs/2505.23020

AgentAlign: Navigating Safety Alignment in the Shift from Informative to Agentic Large Language Models
The acquisition of agentic capabilities has transformed LLMs from "knowledge providers" to "action executors", a trend that while expanding LLMs' capability boundaries, significantly increases their susceptibility to malicious use. Previous work has shown that current LLM-based agents execute numerous malicious tasks even without being attacked, indicating a deficiency in agentic use safety alignment during the post-training phase. To address this gap, we propose AgentAlign, a novel framework t…

Agent-based Liquidity Risk Modelling for Financial Markets
Perukrishnen Vytelingum, Rory Baggott, Namid Stillman, Jianfei Zhang, Dingqiu Zhu, Tao Chen, Justin Lyon
https://arxiv.org/abs/2505.15296

Agent-based Liquidity Risk Modelling for Financial Markets
In this paper, we describe a novel agent-based approach for modelling the transaction cost of buying or selling an asset in financial markets, e.g., to liquidate a large position as a result of a margin call to meet financial obligations. The simple act of buying or selling in the market causes a price impact and there is a cost described as liquidity risk. For example, when selling a large order, there is market slippage -- each successive trade will execute at the same or worse price. When th…

DX100: A Programmable Data Access Accelerator for Indirection
Alireza Khadem, Kamalavasan Kamalakkannan, Zhenyan Zhu, Akash Poptani, Yufeng Gu, Jered Benjamin Dominguez-Trujillo, Nishil Talati, Daichi Fujiki, Scott Mahlke, Galen Shipman, Reetuparna Das
https://arxiv.org/abs/2505.23073

DX100: A Programmable Data Access Accelerator for Indirection
Indirect memory accesses frequently appear in applications where memory bandwidth is a critical bottleneck. Prior indirect memory access proposals, such as indirect prefetchers, runahead execution, fetchers, and decoupled access/execute architectures, primarily focus on improving memory access latency by loading data ahead of computation but still rely on the DRAM controllers to reorder memory requests and enhance memory bandwidth utilization. DRAM controllers have limited visibility to future …