Tootfinder

The UK's FCA plans to lift its ban on offering crypto exchange traded notes to retail investors "to support UK growth and competitiveness" (Ian Allison/CoinDesk)
https://www.coindesk.com/policy/2025/06/06/uk…

A Context-Aware Dual-Metric Framework for Confidence Estimation in Large Language Models
Mingruo Yuan, Shuyi Zhang, Ben Kao
https://arxiv.org/abs/2508.00600 https://

A Context-Aware Dual-Metric Framework for Confidence Estimation in Large Language Models
Accurate confidence estimation is essential for trustworthy large language models (LLMs) systems, as it empowers the user to determine when to trust outputs and enables reliable deployment in safety-critical applications. Current confidence estimation methods for LLMs neglect the relevance between responses and contextual information, a crucial factor in output quality evaluation, particularly in scenarios where background knowledge is provided. To bridge this gap, we propose CRUX (Context-awar…

Async Rust: When to Use It and When to Avoid It
“Asynchronous” (often abbreviated as “async”) is a widely used term in computer science, but its meaning varies depending on the context. […]
🦀 https://fmoya.dev/posts/async-rust/

This https://arxiv.org/abs/2505.14884 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Polar Sparsity: High Throughput Batched LLM Inferencing with Scalable Contextual Sparsity
Accelerating large language model (LLM) inference is critical for real-world deployments requiring high throughput and low latency. Contextual sparsity, where each token dynamically activates only a small subset of the model parameters, shows promise but does not scale to large batch sizes due to union of active neurons quickly approaching dense computation. We introduce Polar Sparsity, highlighting a key shift in sparsity importance from MLP to Attention layers as we scale batch size and seque…

Efficient Multi-Slide Visual-Language Feature Fusion for Placental Disease Classification
Hang Guo, Qing Zhang, Zixuan Gao, Siyuan Yang, Shulin Peng, Xiang Tao, Ting Yu, Yan Wang, Qingli Li
https://arxiv.org/abs/2508.03277

Efficient Multi-Slide Visual-Language Feature Fusion for Placental Disease Classification
Accurate prediction of placental diseases via whole slide images (WSIs) is critical for preventing severe maternal and fetal complications. However, WSI analysis presents significant computational challenges due to the massive data volume. Existing WSI classification methods encounter critical limitations: (1) inadequate patch selection strategies that either compromise performance or fail to sufficiently reduce computational demands, and (2) the loss of global histological context resulting fr…

This https://arxiv.org/abs/2505.10981 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory
Recently, scaling test-time compute on Large Language Models (LLM) has garnered wide attention. However, there has been limited investigation of how various reasoning prompting strategies perform as scaling. In this paper, we focus on a standard and realistic scaling setting: majority voting. We systematically conduct experiments on 6 LLMs $\times$ 8 prompting strategies $\times$ 6 benchmarks. Experiment results consistently show that as the sampling time and computational overhead increase, co…

Sub-Scalp EEG for Sensorimotor Brain-Computer Interface
Timothy B Mahoney, David B Grayden, Sam E John
https://arxiv.org/abs/2506.03423 https://

Sub-Scalp EEG for Sensorimotor Brain-Computer Interface
Objective: To establish sub-scalp electroencephalography (EEG) as a viable option for brain-computer interface (BCI) applications, particularly for chronic use, by demonstrating its effectiveness in recording and classifying sensorimotor neural activity. Approach: Two experiments were conducted in this study. The first aim was to demonstrate the high spatial resolution of sub-scalp EEG through analysis of somatosensory evoked potentials in sheep models. The second focused on the practical appli…

This https://arxiv.org/abs/2311.15919 has been replaced.
link: https://scholar.google.com/scholar?q=a

What Monads Can and Cannot Do with a Few Extra Pages
The delay monad provides a way to introduce general recursion in type theory. To write programs that use a wide range of computational effects directly in type theory, we need to combine the delay monad with the monads of these effects. Here we present a first systematic study of such combinations. We study both the coinductive delay monad and its guarded recursive cousin, giving concrete examples of combining these with well-known computational effects. We also provide general theorems stati…

New computational methods in lattice gauge theory -- quantum computation and tensor networks
Etsuko Itou
https://arxiv.org/abs/2508.03126 https://arxiv.org…

New computational methods in lattice gauge theory -- quantum computation and tensor networks
Lattice QCD calculations have been conducted using large-scale classical computers based on the Lagrangian formalism of field theory for the past 40 years. On the other hand, the advent of quantum computers has brought increasing attention to first-principles computational methods based on the Hamiltonian formalism compatible with these machines. In this talk, we discuss recent results on how to calculate hadronic properties using the Hamiltonian formalism.

Google unveils a Guided Learning mode within its Gemini chatbot to help students and commits $1B over three years to AI education and training efforts in the US (Mark Sullivan/Fast Company)
https://www.fastcompany.com/91380890/google-unveils-n…

Exclusive: Google Gemini adds AI tutoring, heating up the fight for student users
The new tool, and a $1 billion initiative to improve AI education for college-age Americans, will compete against OpenAI’s recently added ChatGPT Study mode.