Tootfinder

Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention
Sarthak Khanna, Armin Berger, David Berghaus, Tobias Deusser, Lorenz Sparrenberg, Rafet Sifa
https://arxiv.org/abs/2508.13327

Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention
We propose STONK (Stock Optimization using News Knowledge), a multimodal framework integrating numerical market indicators with sentiment-enriched news embeddings to improve daily stock-movement prediction. By combining numerical & textual embeddings via feature concatenation and cross-modal attention, our unified pipeline addresses limitations of isolated analyses. Backtesting shows STONK outperforms numeric-only baselines. A comprehensive evaluation of fusion strategies and model configuratio…

Blocklet concatenation: Low-overhead fault-tolerant protocols for fusion-based quantum computation
Daniel Litinski
https://arxiv.org/abs/2506.13619 https:/…

Blocklet concatenation: Low-overhead fault-tolerant protocols for fusion-based quantum computation
We introduce a construction for protocols for fault-tolerant quantum computing based on code concatenation and transversal gates. These protocols can be interpreted as families of quantum circuits of low-weight stabilizer measurements without strict locality constraints, effectively implementing concatenated codes. However, we primarily study these protocols in the context of photonic fusion-based quantum computing (FBQC), where they yield families of fusion networks with constant-sized resourc…

I have been working on a build tool. Again.
This one… I think it’s got legs.
Here it is, concatenating a bunch of text files together:
https://codeberg.org/ooble/um/src/branch/main/tests/cat/oh.um
And here, compiling a simple C program, w…

ConiQ: Enabling Concatenated Quantum Error Correction on Neutral Atom Arrays
Pengyu Liu, Mingkuan Xu, Hengyun Zhou, Hanrui Wang, Umut A. Acar, Yunong Shi
https://arxiv.org/abs/2508.05779

ConiQ: Enabling Concatenated Quantum Error Correction on Neutral Atom Arrays
Recent progress on concatenated codes, especially many-hypercube codes, achieves unprecedented space efficiency. Yet two critical challenges persist in practice. First, these codes lack efficient implementations of addressable logical gates. Second, the required high degree of parallelism and long-range interactions pose significant challenges for current hardware platforms. In this paper, we propose an efficient compilation approach for concatenated codes, specifically many-hypercube codes, ta…

Tangent Cones of Concatenated Numerical Semigroups
Ranjana Mehta, Joydip Saha, Indranath Sengupta
https://arxiv.org/abs/2506.09400 https://

Tangent Cones of Concatenated Numerical Semigroups
We study the tangent cone at the origin and the Hilbert series for a family of numerical semigroups generated by concatenation of arithmetic sequences. We prove that all the concatenation classes have Cohen-Macaulay tangent cones except the symmetric class, however, the symmetric class does satisfy Rossi's conjecture.

Autonomous life-like behavior emerging in active and flexible microstructures
Mengshi Wei, Daniela J. Kraft
https://arxiv.org/abs/2506.15198 https://

Autonomous life-like behavior emerging in active and flexible microstructures
Many organisms leverage an interplay between shape and activity to generate motion and adapt to their environment. Embedding such feedback into synthetic microrobots could eliminate the need for sensors, software, and actuators, yet current realizations are either active but rigid, or flexible but passive. Here, we introduce micrometer-scale structures that integrate both activity and flexibility by 3D microprinting concatenated units and actuating them with an AC electric field. This minimal y…

Concatenated palindromes 🌮 🌮
#NoKings 🐈

There and Back Again: Revisiting the Failure of Concatenation in Mittag-Leffler Functions
Paulo M. Carvalho-Neto, Cesar E. T. Ledesma
https://arxiv.org/abs/2508.05788 https://…

There and Back Again: Revisiting the Failure of Concatenation in Mittag-Leffler Functions
The function $t \mapsto E_α(λt^α)$ is widely regarded as the fractional analogue of the exponential function, yet its algebraic properties remain poorly understood. In particular, standard references lack a rigorous proof of the failure of the semigroup property. In this work, we fill this gap by providing an analytical proof that the semigroup property holds if and only if either $α= 1$ or $λ= 0$. Our result establishes a precise criterion for when Mittag-Leffler dynamics are compatible w…

DMCIE: Diffusion Model with Concatenation of Inputs and Errors to Improve the Accuracy of the Segmentation of Brain Tumors in MRI Images
Sara Yavari, Rahul Nitin Pandya, Jacob Furst
https://arxiv.org/abs/2507.00983

DMCIE: Diffusion Model with Concatenation of Inputs and Errors to Improve the Accuracy of the Segmentation of Brain Tumors in MRI Images
Accurate segmentation of brain tumors in MRI scans is essential for reliable clinical diagnosis and effective treatment planning. Recently, diffusion models have demonstrated remarkable effectiveness in image generation and segmentation tasks. This paper introduces a novel approach to corrective segmentation based on diffusion models. We propose DMCIE (Diffusion Model with Concatenation of Inputs and Errors), a novel framework for accurate brain tumor segmentation in multi-modal MRI scans. We e…

Exploring Cross-Utterance Speech Contexts for Conformer-Transducer Speech Recognition Systems
Mingyu Cui, Mengzhe Geng, Jiajun Deng, Chengxi Deng, Jiawen Kang, Shujie Hu, Guinan Li, Tianzi Wang, Zhaoqing Li, Xie Chen, Xunying Liu
https://arxiv.org/abs/2508.10456

Exploring Cross-Utterance Speech Contexts for Conformer-Transducer Speech Recognition Systems
This paper investigates four types of cross-utterance speech contexts modeling approaches for streaming and non-streaming Conformer-Transformer (C-T) ASR systems: i) input audio feature concatenation; ii) cross-utterance Encoder embedding concatenation; iii) cross-utterance Encoder embedding pooling projection; or iv) a novel chunk-based approach applied to C-T models for the first time. An efficient batch-training scheme is proposed for contextual C-Ts that uses spliced speech utterances withi…