collaborators

9 papers

cs.LG2026

ZeroSiam: An Efficient Asymmetry for Test-Time Entropy Optimization without Collapse

Guohao Chen, Shuaicheng Niu, Deyu Chen +5

Test-time entropy minimization helps adapt a model to novel environments and incentivize its reasoning capability, unleashing the model's potential during inference by allowing it…

cs.AI2026

SDFlow: Similarity-Driven Flow Matching for Time Series Generation

Wei Li, Shibo Feng, Pengcheng Wu +3

Vector quantization (VQ) with autoregressive (AR) token modeling is a widely adopted and highly competitive paradigm for time-series generation. However, such models are fundamenta…

cs.AI2026

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…

cs.SD2025

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…

cs.CL2025

NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction

Qichao Wang, Ziqiao Meng, Wenqian Cui +6

Inspired by the impressive capabilities of GPT-4o, there is growing interest in enabling speech language models (SLMs) to engage in natural, fluid spoken interactions with humans.…

cs.NE2025

Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity

Wanjin Feng, Xingyu Gao, Wenqian Du +4

Spiking Neural Networks (SNNs) often suffer from high time complexity due to the sequential processing of spikes, making training computationally expensive. In this pape…