Tootfinder

DoSReMC: Domain Shift Resilient Mammography Classification using Batch Normalization Adaptation
U\u{g}urcan Aky\"uz, Deniz Katircioglu-\"Ozt\"urk, Emre K. S\"usl\"u, Burhan Kele\c{s}, Mete C. Kaya, Gamze Durhan, Meltem G. Akp{\i}nar, Figen B. Demirkaz{\i}k, G\"ozde B. Akar
https://arxiv.org/abs/2508.15452

DoSReMC: Domain Shift Resilient Mammography Classification using Batch Normalization Adaptation
Numerous deep learning-based solutions have been developed for the automatic recognition of breast cancer using mammography images. However, their performance often declines when applied to data from different domains, primarily due to domain shift - the variation in data distributions between source and target domains. This performance drop limits the safe and equitable deployment of AI in real-world clinical settings. In this study, we present DoSReMC (Domain Shift Resilient Mammography Class…

O amarelinho, ex-prisioneiro, apareceu agora hš pouco. Dš pra perceber com nitidez como ele estš mais magro e como seu pelo estš menos saudšvel do que costumava ser.
https://social.linux.pizza/@matematico314/115357678350152632

PAC: Pronunciation-Aware Contextualized Large Language Model-based Automatic Speech Recognition
Li Fu, Yu Xin, Sunlu Zeng, Lu Fan, Youzheng Wu, Xiaodong He
https://arxiv.org/abs/2509.12647

PAC: Pronunciation-Aware Contextualized Large Language Model-based Automatic Speech Recognition
This paper presents a Pronunciation-Aware Contextualized (PAC) framework to address two key challenges in Large Language Model (LLM)-based Automatic Speech Recognition (ASR) systems: effective pronunciation modeling and robust homophone discrimination. Both are essential for raw or long-tail word recognition. The proposed approach adopts a two-stage learning paradigm. First, we introduce a pronunciation-guided context learning method. It employs an interleaved grapheme-phoneme context modeling …

Gay Times CEO Tag Warner says his outlet is facing "good old-fashioned discrimination" from advertisers amid DEI criticism; other LGBTQ publishers agree (Michael Savage/The Guardian)
https://www.theguardian.com/media/2025/aug/31/lgbtq-media-advertisin…

Trump’s Gaza peace plan leaves door ajar for Palestinian state
Some elements of the U.S. proposal are comically specific.
“Once all the hostages have been released,” it reads,
“Israel will release 250 life sentence prisoners plus 1,700 Gazans who were detained after October 7. …
For every Israeli hostage whose remains are released, Israel will release the remains of 15 deceased Gazans.”

The proposal says that “upon acceptance of this agreement,
full aid…

Trump’s Gaza peace plan leaves door ajar for Palestinian state
Trump’s 21-point peace plan includes Hamas disarmament, an international security force and a “Trump development plan” to rebuild the shattered enclave. But Israel might balk at some proposals.

Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training
Anthony P. Addison, Felix Wagner, Wentian Xu, Natalie Voets, Konstantinos Kamnitsas
https://arxiv.org/abs/2509.09290

Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training
Segmentation models are important tools for the detection and analysis of lesions in brain MRI. Depending on the type of brain pathology that is imaged, MRI scanners can acquire multiple, different image modalities (contrasts). Most segmentation models for multimodal brain MRI are restricted to fixed modalities and cannot effectively process new ones at inference. Some models generalize to unseen modalities but may lose discriminative modality-specific information. This work aims to develop a m…

Characterizing IceTop Response to Low-Energy Air Showers
Yanee Tangjai (for the IceCube Collaboration), Agnieszka Leszczynska (for the IceCube Collaboration), Tatphicha Promfu (for the IceCube Collaboration), Achara Seripienlert (for the IceCube Collaboration), Serap Tilav (for the IceCube Collaboration)
https://arxiv.org/abs/2510.10485

Characterizing IceTop Response to Low-Energy Air Showers
This study evaluates the response of the IceTop tanks to low-energy air showers in the GeV to TeV energy range based on simulated and measured count rates. Correlating this response with primary cosmic rays provides a tool to study Galactic and solar cosmic-ray flux modulations, particularly for solar particle events. We present long-term behavior of the IceTop scaler rates for a range of discriminator thresholds to better understand and calibrate the detector's response to changing environment…

Quantum Dynamics and Information Measures in PT and Anti-PT-Symmetric Systems
Amir Ahmadi, Roozbeh H. Asgari, Javad T. Firouzjaee
https://arxiv.org/abs/2508.03169 https://

Quantum Dynamics and Information Measures in PT and Anti-PT-Symmetric Systems
In this study, we investigate qubit dynamics under PT and Anti-PT-symmetric non-Hermitian Hamiltonians, focusing on phase evolution, decoherence, quantum speed limits (QSL), and Rényi entanglement entropies. Using similarity transformations and Dyson maps, we analyze the reduced density matrix evolution in bosonic environments. Anti-PT-symmetric systems show enhanced robustness against decoherence, with slower entropy growth and longer coherence times compared to PT-symmetric counterparts. QSL…

Ok, o cansaço estš começando a bater forte. Mas quero pelo menos fazer o gabarito da prova de terça. Final de período é a pior época do semestre, não dš pra fazer corpo mole. Que o café faça seu milagre agora rs.

MLSD: A Novel Few-Shot Learning Approach to Enhance Cross-Target and Cross-Domain Stance Detection
Parush Gera, Tempestt Neal
https://arxiv.org/abs/2509.03725 https://

MLSD: A Novel Few-Shot Learning Approach to Enhance Cross-Target and Cross-Domain Stance Detection
We present the novel approach for stance detection across domains and targets, Metric Learning-Based Few-Shot Learning for Cross-Target and Cross-Domain Stance Detection (MLSD). MLSD utilizes metric learning with triplet loss to capture semantic similarities and differences between stance targets, enhancing domain adaptation. By constructing a discriminative embedding space, MLSD allows a cross-target or cross-domain stance detection model to acquire useful examples from new target domains. We …