7 accepted papers
Meteorological downscaling is crucial for high-resolution regional climate forecasting and disaster early warning. While neural operators have emerged as a promising paradigm for modeling complex spatiotemporal mappings, existing frameworks often struggle with spherical manifold geometric distortion
Climate downscaling is crucial for detailed small- scale analysis and for acquiring climate data in regions without weather stations. Operator learning has proven potential for this task. However, several challenges remain in operator learning, such as multimodal fusion, spatiotemporal fusion and in…
Large Language Models (LLMs) demonstrate impressive zero-shot performance across a wide range of natural language processing tasks. Integrating various modality encoders further expands their capabilities, giving rise to Multimodal Large Language Models (MLLMs) that process not only text but also vi…
The deep operator networks (DON), a class of neural operators that learn mappings between function spaces, have recently emerged as surrogate models for parametric partial differential equations (PDEs). However, their full potential for accurately approximating general black-box PDEs remains underex
Wireless acoustic sensor network (WASN) has become a useful platform for monitoring acoustic scenes and sound acquisition. It is likely that many acoustic devices have a marginal impact on performance, which facilitates a necessity of optimizing the tradeoff between performance and computational loa…
Direction-based target speaker extraction (TSE) attracts a constant attention due to the convenience of direction acquisition over assistive video or enrollment audio. The direction clue heavily affects the TSE performance, which might be more seriously in the case of binaural setups due to the smal…
Target speaker extraction (TSE) based on direction of arrival (DOA) has a wide range of applications in e.g., remote conferencing, hearing aids, in-car speech interaction. Due to the inherent phase uncertainty, existing TSE methods usually suffer from speaker confusion within specific frequency band…