We introduce a voice-agentic framework that learns one critical omni-understanding skill: knowing when to trust itself versus when to consult external audio perception. Our work is motivated by a crucial yet counterintuitive finding: naively fine-tuning an omni-model on both speech recognition and external sound understanding tasks often degrades performance, as the model can be easily misled by noisy hypotheses. To address this, our framework, Speech-Hands, recasts the problem as an explicit self-reflection decision. This learnable reflection primitive proves effective in preventing the model from being derailed by flawed external candidates. We show that this agentic action mechanism generalizes naturally from speech recognition to complex, multiple-choice audio reasoning. Across the OpenASR leaderboard, Speech-Hands consistently outperforms strong baselines by 12.1% WER on seven benchmarks. The model also achieves 77.37% accuracy and high F1 on audio QA decisions, showing robust generalization and reliability across diverse audio question answering datasets. By unifying perception and decision-making, our work offers a practical path toward more reliable and resilient audio intelligence.
OmniPath: A Multi-Modal Agentic Framework for Auditing Wheelchair Accessibility
Causal AI Lab, Department of Information Systems, University of Maryland Baltimore County（因果AI实验室，信息系统系，马里兰大学巴尔的摩分校）；Department of Computer Science & Software Engineering, Miami University（计算机科学与软件工程系，迈阿密大学）
OmniVL-Guard Pro: A Tool-Augmented Agent for Omnibus Vision-Language Forensics
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China（合肥工业大学计算机科学与信息工程学院）；Wuhan University, Wuhan, China（武汉大学）；Lab for Intelligence and visiON (LION)（智能与视觉实验室）；Xi'an Jiaotong University（西安交通大学）
TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents
Nanjing University（南京大学）；Huazhong University of Science and Technology（华中科技大学）；Southwest Jiaotong University（西南交通大学）；The Chinese University of Hong Kong（香港中文大学）
From Code-Centric to Intent-Centric Software Engineering: A Reflexive Thematic Analysis of Generative AI, Agentic Systems, and Engineering Accountability
Dependency-Aware Reward Shaping for Agentic Reinforcement Learning
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；National University of Singapore（新加坡国立大学）；Zhejiang University（浙江大学）；University of Rochester（罗切斯特大学）
ParaBridge: Bridging Paralinguistic Perception and Dialogue Behavior in Speech Language Models
The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Tencent Hunyuan（腾讯混元）；Shenzhen Loop Area Institute（深圳河套学院）；Amphion Technology Co., Ltd.（Amphion科技有限公司）；Tsinghua University（清华大学）
LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis
Key Laboratory of Intelligent Information Processing Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)（智能信息处理重点实验室，计算技术研究所，中国科学院）；Key Laboratory of AI Safety, Chinese Academy of Sciences（人工智能安全重点实验室，中国科学院）；University of Chinese Academy of Sciences, Beijing, China（中国科学院大学，北京，中国）
Native Active Perception as Reasoning for Omni-Modal Understanding
The Chinese University of Hong Kong（香港中文大学）；Shanghai Jiao Tong University（上海交通大学）；Nanyang Technological University（南洋理工大学）；Qwen Team, Alibaba Group（阿里巴巴集团Qwen团队）
ESPnet-SpeechLM: An Open Speech Language Model Toolkit
Carnegie Mellon University（卡内基梅隆大学）；Mitsubishi Electric Research Laboratories（三菱电机研究所）；LY Corporation（LY公司）；Renmin University of China（中国人民大学）；Brno University of Technology（布尔诺理工大学）；NVIDIA Research（英伟达研究院）
AV-EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Omni-modal LLMS with Audio-visual Cues
UC Berkeley（加州大学伯克利分校）；South China University of Technology（华南理工大学）；Zhejiang University（浙江大学）；National Taiwan University（台湾大学）；University of Southern California（美国南加州大学）
From Reliable Text to Real Voices: Trust-Aware Progressive Adaptation for Low-Resource TTS
Beijing Logic Intelligence Technology（北京逻辑智能科技有限公司）；University of Washington（华盛顿大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；University of California, USA（加州大学）；Northwestern University, USA（西北大学）
Omni Demand Understanding: A Benchmark for Contextual User-Intent Inference in Multimodal Interaction
Shanghai Jiao Tong University（上海交通大学）；Shanghai Innovation Institute（上海创新研究院）；Alibaba Token Hub, Alibaba Group（阿里巴巴集团阿里巴巴Token Hub）；The Chinese University of Hong Kong（香港中文大学）；Tsinghua University（清华大学）；Hong Kong Polytechnic University（香港理工大学）；Nankai University（南开大学）；Johns Hopkins University（约翰斯·霍普金斯大学）
