47 citations · 115 across the 22 of their papers we have counts for
7 papers · 1 filter
Cocktail-Talker: Multi-Speaker Dialog Modeling in Noisy Social Environments with Turn Action GRPO
Xilin Jiang, Riki Shimizu, Sukru Samet Dindar +3
Spoken dialog systems are typically designed for clean, dyadic interactions in which a single user and an assistant take turns speaking. Real-world social conversations, however, a…
Sympatheia: Emotionally Adaptive Voice Assistant with Continuous Affect Conditioning
Sukru Samet Dindar, Riki Shimizu, Xilin Jiang +1
Empathetic spoken dialogue systems must infer a user's emotional state to respond appropriately, yet everyday speech often carries weak, neutral, or ambiguous affective cues. To ad…
AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking
Xilin Jiang, Qiaolin Wang, Junkai Wu +30
Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examine whether AI models can understand suc…
SightSound-R1: Cross-Modal Reasoning Distillation from Vision to Audio Language Models
Qiaolin Wang, Xilin Jiang, Linyang He +2
While large audio-language models (LALMs) have demonstrated state-of-the-art audio understanding, their reasoning capability in complex soundscapes still falls behind large vision-…
Bridging Ears and Eyes: Analyzing Audio and Visual Large Language Models to Humans in Visible Sound Recognition and Reducing Their Sensory Gap via Cross-Modal Distillation
Xilin Jiang, Junkai Wu, Vishal Choudhari +1
Audio large language models (LLMs) are considered experts at recognizing sound objects, yet their performance relative to LLMs in other sensory modalities, such as visual or audio-…
AAD-LLM: Neural Attention-Driven Auditory Scene Understanding
Xilin Jiang, Sukru Samet Dindar, Vishal Choudhari +6
Auditory foundation models, including auditory large language models (LLMs), process all sound inputs equally, independent of listener perception. However, human auditory perceptio…
Compute and memory efficient universal sound source separation
Efthymios Tzinis, Zhepei Wang, Xilin Jiang +1
Recent progress in audio source separation lead by deep learning has enabled many neural network models to provide robust solutions to this fundamental estimation problem. In this…