1 citations · 1 across the 8 of their papers we have counts for
9 papers
JIT-Agent: Scaling Harness Intelligence via Just-in-Time Harness Evolution
Guibin Zhang, Leo Lu, Fangzhou Xie +15
Agent capability is not determined by the model alone. The agent harness, encompassing memory management, planning strategy, action protocol, and tool/skill orchestration, can domi…
VoiceMem: Streaming Dual-Brain Memory for Real-Time Interaction
Zhifei Xie, Jiaqi Lang, Ze An +7
Conversational systems, such as duplex speech language models (SLMs), still lack a streaming, accurate, and empathetic memory system as their soul. We introduce VoiceMem, a simple…
MMAE: A Massive Multitask Audio Editing Benchmark
Ziyang Ma, Ruiqi Yan, Ruiyang Xu +35
We introduce MMAE, a Massive Multitask Audio Editing benchmark, serving as the first comprehensive evaluation testbed designed for general-purpose instruction-based audio editing.…
Audio Interaction Model
Zhifei Xie, Zihang Liu, Ze An +8
Audio is continuous and interactive, yet most Large Audio Language Models (LALMs) remain offline and streaming systems usually specialize in ASR or spoken dialogue. We formalize th…
Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation
Zhifei Xie, Kaiyu Pang, Haobin Zhang +4
Despite rapid advances in automatic speech recognition (ASR) and large audio-language models, robust recognition in real-world environments remains limited by an "acoustic robustne…
Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation
Fangda Ye, Zhifei Xie, Yuxin Hu +5
Recent agentic search frameworks enable deep research via iterative planning and retrieval, reducing hallucinations and enhancing factual grounding. However, they remain text-centr…
PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory
Zhifei Xie, Zongzheng Hu, Fangda Ye +10
Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive agent: depth, complexity, ambigui…
Mini-Omni-Reasoner: Token-Level Thinking-in-Speaking in Large Speech Models
Zhifei Xie, Ziyang Ma, Zihang Liu +7
Reasoning is essential for effective communication and decision-making. While recent advances in LLMs and MLLMs have shown that incorporating explicit reasoning significantly impro…
Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models
Zhifei Xie, Mingbao Lin, Zihang Liu +3
Recent advancements in multimodal reasoning have largely overlooked the audio modality. We introduce Audio-Reasoner, a large-scale audio language model for deep reasoning in audio…