Audio-Visual Question Answering (AVQA) is a complex multi-modal reasoning task, demanding intelligent systems to accurately respond to natural language queries based on audio-video input pairs. Nevertheless, prevalent AVQA approaches are prone to overlearning dataset biases, resulting in poor robustness. Furthermore, current datasets may not provide a precise diagnostic for these methods. To tackle these challenges, firstly, we propose a novel dataset, MUSIC-AVQA-R, crafted in two steps: rephrasing questions within the test split of a public dataset (MUSIC-AVQA) and subsequently introducing distribution shifts to split questions. The former leads to a large, diverse test space, while the latter results in a comprehensive robustness evaluation on rare, frequent, and overall questions.

Linear systems are the bedrock of virtually all numerical computation. Machine learning poses specific challenges for the solution of such systems due to their scale, characteristic structure, stochasticity and the central role of uncertainty in the field. Unifying earlier work we propose a class of probabilistic linear solvers which jointly infer the matrix, its inverse and the solution from matrix-vector product observations. This class emerges from a fundamental set of desiderata which constrains the space of possible algorithms and recovers the method of conjugate gradients under certain conditions. We demonstrate how to incorporate prior spectral information in order to calibrate uncertainty and experimentally showcase the potential of such solvers for machine learning.

Malaysia declared it'll build a first-of-its-kind AI system powered by Huawei Technologies chips, only to distance itself from that statement a day later, underscoring the Asian nation's delicate position in the U.S.-Chinese AI race. Deputy Minister of Communications Teo Nie Ching said in a speech Monday her country would be the first to activate an unspecified class of Huawei "Ascend GPU-powered AI servers at national scale." Malaysia would deploy 3,000 units of Huawei's primary AI offering by 2026, she said in prepared remarks reviewed by Bloomberg News. Chinese startup DeepSeek would also make one of its AI models available to the Southeast Asian country, the official added.

Former United States President Joe Biden was not diagnosed with prostate cancer before last week, and received his "last known" blood test for the disease more than a decade ago, his office has said. The Biden camp's statement on Tuesday came as critics, including current President Donald Trump, stoked scepticism over the timing of the diagnosis, which has reanimated questions about whether the former president misled the public about his health while in office. "President Biden's last known PSA was in 2014," Biden's office said in the brief statement, referring to the prostate-specific antigen test used to detect prostate cancer. "Prior to Friday, President Biden had never been diagnosed with prostate cancer." On Monday, Trump said he was "surprised" that the public had not been notified about Biden's diagnosis "a long time ago".

We thank reviewers for their valuable comments. We will incorporate all feedback in our final manuscript. EBMs generate more diverse samples. Extending the space of concepts requires retraining the network. This can miss interaction effects between parts (such as shadow casting).

While this "data-driven" way of learning stochastic processes has proven to handle various types of data,