Tootfinder

This https://arxiv.org/abs/2505.19746 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Improving Heart Rejection Detection in XPCI Images Using Synthetic Data Augmentation
Accurate identification of acute cellular rejection (ACR) in endomyocardial biopsies is essential for effective management of heart transplant patients. However, the rarity of high-grade rejection cases (3R) presents a significant challenge for training robust deep learning models. This work addresses the class imbalance problem by leveraging synthetic data generation using StyleGAN to augment the limited number of real 3R images. Prior to GAN training, histogram equalization was applied to sta…

Revisiting Noise-adaptive Transpilation in Quantum Computing: How Much Impact Does it Have?
Yuqian Huo, Jinbiao Wei, Christopher Kverne, Mayur Akewar, Janki Bhimani, Tirthak Patel
https://arxiv.org/abs/2507.01195

Revisiting Noise-adaptive Transpilation in Quantum Computing: How Much Impact Does it Have?
Transpilation, particularly noise-aware optimization, is widely regarded as essential for maximizing the performance of quantum circuits on superconducting quantum computers. The common wisdom is that each circuit should be transpiled using up-to-date noise calibration data to optimize fidelity. In this work, we revisit the necessity of frequent noise-adaptive transpilation, conducting an in-depth empirical study across five IBM 127-qubit quantum computers and 16 diverse quantum algorithms. Our…

Modelling the evolution of flow-induced anisotropy of concentrated suspensions
Pappu Acharya, Romain Mari
https://arxiv.org/abs/2506.05222 https://

Modelling the evolution of flow-induced anisotropy of concentrated suspensions
Suspensions, which exhibit complex behaviors such as shear thickening, thinning, and jamming, are prevalent in nature and industry. However, predicting the mechanical properties of concentrated suspensions, in both steady state and the transient regime, remains a significant challenge, impacting product quality and process efficiency. In this study, we focus on developing a robust theoretical framework to explain how flow history governs the anisotropy of mechanical responses in suspensions of …

DIJE: Dense Image Jacobian Estimation for Robust Robotic Self-Recognition and Visual Servoing
Yasunori Toshimitsu, Kento Kawaharazuka, Akihiro Miki, Kei Okada, Masayuki Inaba
https://arxiv.org/abs/2507.00446

DIJE: Dense Image Jacobian Estimation for Robust Robotic Self-Recognition and Visual Servoing
For robots to move in the real world, they must first correctly understand the state of its own body and the tools that it holds. In this research, we propose DIJE, an algorithm to estimate the image Jacobian for every pixel. It is based on an optical flow calculation and a simplified Kalman Filter that can be efficiently run on the whole image in real time. It does not rely on markers nor knowledge of the robotic structure. We use the DIJE in a self-recognition process which can robustly disti…

This https://arxiv.org/abs/2406.07186 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Information Aggregation with Costly Information Acquisition
We study information aggregation in a dynamic trading model with partially informed traders. Ostrovsky [2012] showed that 'separable' securities aggregate information in all equilibria, however, separability is not robust to small changes in the traders' private information. To remedy this problem, we enhance the model by allowing traders to acquire signals with cost $κ$, in every period. We show that '$κ$ separable securities' aggregate information and, as the cost decreases, nearly all secu…

Enhancing Lyrics Transcription on Music Mixtures with Consistency Loss
Jiawen Huang, Felipe Sousa, Emir Demirel, Emmanouil Benetos, Igor Gadelha
https://arxiv.org/abs/2506.02339

Enhancing Lyrics Transcription on Music Mixtures with Consistency Loss
Automatic Lyrics Transcription (ALT) aims to recognize lyrics from singing voices, similar to Automatic Speech Recognition (ASR) for spoken language, but faces added complexity due to domain-specific properties of the singing voice. While foundation ASR models show robustness in various speech tasks, their performance degrades on singing voice, especially in the presence of musical accompaniment. This work focuses on this performance gap and explores Low-Rank Adaptation (LoRA) for ALT, investig…

Evaluating the Robustness of Dense Retrievers in Interdisciplinary Domains
Sarthak Chaturvedi, Anurag Acharya, Rounak Meyur, Koby Hayashi, Sai Munikoti, Sameera Horawalavithana
https://arxiv.org/abs/2506.21581

Evaluating the Robustness of Dense Retrievers in Interdisciplinary Domains
Evaluation benchmark characteristics may distort the true benefits of domain adaptation in retrieval models. This creates misleading assessments that influence deployment decisions in specialized domains. We show that two benchmarks with drastically different features such as topic diversity, boundary overlap, and semantic complexity can influence the perceived benefits of fine-tuning. Using environmental regulatory document retrieval as a case study, we fine-tune ColBERTv2 model on Environment…

Constraining the Extragalactic Magnetic Field: Auger Data Meet UHECR Propagation Modeling
Ala'a AL-Zetoun, Arjen van Vliet, Andrew M. Taylor, Walter Winter
https://arxiv.org/abs/2506.16169

Constraining the Extragalactic Magnetic Field: Auger Data Meet UHECR Propagation Modeling
Recent analyses from the Pierre Auger Collaboration suggest correlations between the arrival directions of Ultra-High-Energy Cosmic Rays (UHECRs) and catalogs of starburst galaxies (SGBs) and jetted active galactic nuclei (AGNs). We revisit these analyses using the same methodology as \auger , but explicitly incorporating UHECR deflections in turbulent extragalactic magnetic fields (EGMFs). We demonstrate that while for SBGs the same sources as for the generic \auger\ analysis dominate the cata…

The KELT-7b atmospheric thermal-inversion conundrum revisited with CHEOPS, TESS, and additional data
Z. Garai, A. Krenn, P. E. Cubillos, G. Bruno, A. M. S. Smith, T. G. Wilson, A. Brandeker, M. N. G\"unther, A. Heitzmann, L. Carone, V. Singh, M. Lendl, O. D. S. Demangeon, Y. Alibert, R. Alonso, J. Asquier, T. B\'arczy, D. Barrado, S. C. Barros, W. Baumjohann, W. Benz, N. Billot, L. Borsato, C. Broeg, A. Collier Cameron, A. C. M. Correia, Sz. Csizmadia, M. B. Davies, M. Deleuil…

The KELT-7b atmospheric thermal-inversion conundrum revisited with CHEOPS, TESS, and additional data
Ultrahot Jupiters are predicted to show inverted temperature-pressure (T-P) profiles in the presence of optical absorbers such as TiO and VO. An inverted T-P profile of KELT-7b was recently detected, in line with these predictions, but such diagnoses are known to be model-dependent. We used CHEOPS, TESS, and literature data to characterize the atmosphere of KELT-7b, reassess its T-P profile, measure its albedo, and search for distortions in its CHEOPS transit light curve due to stellar rotation…

Exploring Year-timescale Gamma-ray Quasi-Periodic Oscillations in Blazars: Evidence for Supermassive Binary Black Holes Scenario
Ajay Sharma, Sakshi Chaudhary, Aishwarya Sarath, Debanjan Bose
https://arxiv.org/abs/2505.23697

Exploring Year-timescale Gamma-ray Quasi-Periodic Oscillations in Blazars: Evidence for Supermassive Binary Black Holes Scenario
A comprehensive analysis of quasi-periodic oscillations (QPOs) in the gamma-ray emissions of blazars. Utilizing 15 years of Fermi-LAT observations of seven blazars in our sample, we identify both long-term and transient quasi-periodic oscillations in the gamma-ray light curves, with timescales ranging from a few months to years. These periodicities were detected using the Lomb-Scargle periodogram and REDFIT techniques. To robustly evaluate the statistical significance of the quasi-periodic sign…