Tootfinder

"The destruction of the climate by industrial processes is a real-world problem. If programming language selection has no impact on it, then maybe we’re all just wasting our time, creating shiny consumer distractions to make the last few years of humanity that little more palatable for the richest 1% of the world’s human population."

Choosing A Programming Language
Selecting the correct programming language for a particular task often feels like a bunfight. Suggestions are thrown around based on the individual's preferences and desires. The experience is very likely to leave one feeling that programming is an art, rather than a science.

Next stop on our NLP timeline (as part of the #ISE2025 lecture) was Terry Winograd's SHRDLU, an early natural language understanding system developed in 1968-70 that could manipulate blocks in a virtual world.
Winograd, T. Procedures as a Representation for Data in a Computer Program for Understanding Natural Language. MIT AI Technical Report 235.

This https://arxiv.org/abs/2506.04907 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Verbose ListOps (VLO): Beyond Long Context -- Unmasking LLM's Reasoning Blind Spots
Large Language Models (LLMs), whilst great at extracting facts from text, struggle with nested narrative reasoning. Existing long context and multi-hop QA benchmarks inadequately test this, lacking realistic distractors or failing to decouple context length from reasoning complexity, masking a fundamental LLM limitation. We introduce Verbose ListOps, a novel benchmark that programmatically transposes ListOps computations into lengthy, coherent stories. This uniquely forces internal computation …

from my link log —
10 years of stable Rust: an infrastructure story.
https://rustfoundation.org/media/10-years-of-stable-rust-an-infrastructure-story/
saved 2025-05-15

10 Years of Stable Rust: An Infrastructure Story - The Rust Foundation
A note from the Rust Foundation: Today, May 15, 2025, marks 10 years since the first stable release of Rust. To commemorate this milestone, we are excited to share the following guest blog contributed by Graydon Hoare, initial author of the Rust programming language.   Rust turns 10 today, or at…

DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
Jingyu Xiao, Ming Wang, Man Ho Lam, Yuxuan Wan, Junliang Liu, Yintong Huo, Michael R. Lyu
https://arxiv.org/abs/2506.06251

DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in automated front-end engineering, e.g., generating UI code from visual designs. However, existing front-end UI code generation benchmarks have the following limitations: (1) While framework-based development becomes predominant in modern front-end programming, current benchmarks fail to incorporate mainstream development frameworks. (2) Existing evaluations focus solely on the UI code generation task, whereas p…

Spin-lattice entanglement in $\mathbf{CoPS}_3$
Thuc T. Mai, Amber McCreary, K. F. Garrity, Rebecca L. Dally, Sambridhi Shah, Bryan C. Chakoumakos, Md Nasim Afroj Taj, Jeffrey W. Lynn, Michael A. McGuire, Benjamin S. Conner, Mona Zebarjadi, Janice L. Musfeldt, Angela R. Hight Walker, Rahul Rao, Michael A. Susner
https://arxiv.org…

Spin-lattice entanglement in $\mathbf{CoPS}_3$
Complex chalcogenides in the $M$PS$_3$ family of materials ($M$ = Mn, Fe, Co, and Ni) display remarkably different phase progressions depending upon the metal center orbital filling, character of the P-P linkage, and size of the van der Waals gap. There is also a stacking pattern and spin state difference between the lighter and heavier transition metal-containing systems that places CoPS$_3$ at the nexus of these activities. Despite these unique properties, this compound is under-explored. Her…

"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."

RewardBench 2: Advancing Reward Model Evaluation
Saumya Malik, Valentina Pyatkin, Sander Land, Jacob Morrison, Noah A. Smith, Hannaneh Hajishirzi, Nathan Lambert
https://arxiv.org/abs/2506.01937

RewardBench 2: Advancing Reward Model Evaluation
Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target for optimization across instruction following, reasoning, safety, and more domains. The community has begun establishing best practices for evaluating reward models, from the development of benchmarks that test capabilities in specific skill areas to others that test agreement with human preferences. At the same time, progress in evaluation has not…

This https://arxiv.org/abs/2505.15004 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

EASY: Emotion-aware Speaker Anonymization via Factorized Distillation
Emotion plays a significant role in speech interaction, conveyed through tone, pitch, and rhythm, enabling the expression of feelings and intentions beyond words to create a more personalized experience. However, most existing speaker anonymization systems employ parallel disentanglement methods, which only separate speech into linguistic content and speaker identity, often neglecting the preservation of the original emotional state. In this study, we introduce EASY, an emotion-aware speaker an…

Synthesizing Performance Constraints for Evaluating and Improving Code Efficiency
Jun Yang, Cheng-Chi Wang, Bogdan Alexandru Stoica, Kexin Pei
https://arxiv.org/abs/2505.23471

Synthesizing Performance Constraints for Evaluating and Improving Code Efficiency
Large Language Models (LLMs) have been increasingly used to optimize code efficiency. Evaluating their effectiveness and further suggesting optimization opportunities often rely on high-quality tests to demonstrate the performance bottlenecks presented in the program. However, existing approaches rely on a limited set of hand-curated inputs or LLM-generated uninteresting length-stressing tests, failing to reveal more nuanced optimization opportunities. We present WEDGE, a framework for generati…