Tootfinder

From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training
Tianqiao Liu, Xueyi Li, Hao Wang, Haoxuan Li, Zhichao Chen, Weiqi Luo, Zitao Liu
https://arxiv.org/abs/2509.20072

From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training
Recent advances in large language models have attracted significant interest in extending their capabilities to multimodal scenarios, particularly for speech-in speech-out conversational systems. However, existing multimodal models handling interleaved audio and text, such as MOSHI require complex multi stage training pipelines, incurring substantial computational costs. Moreover, these models uniformly apply autoregressive generation to both text and audio tokens, overlooking a fundamental asy…

Green's function and volume noncollapsing estimates for the K\"ahler-Ricci flow
Weiqi Zhang, Yashan Zhang
https://arxiv.org/abs/2508.13646 https://

Green's function and volume noncollapsing estimates for the Kähler-Ricci flow
We prove a local volume noncollapsing property for the long-time Kähler-Ricci flow on a minimal Kähler manifold, improving previous results of Guo-Phong-Song-Sturm, Guedj-Tô and Vu. Similar result is also proved for a twisted Kähler-Ricci flow on non-minimal Kähler manifolds. In the course of proof, we develop new Green's function estimates for a general Kähler family under the $L^{p>1}$ and $L^1(\log L)^{q>n}$ volume density conditions.

Multi-Granularity Distribution Modeling for Video Watch Time Prediction via Exponential-Gaussian Mixture Network
Xu Zhao, Ruibo Ma, Jiaqi Chen, Weiqi Zhao, Ping Yang, Yao Hu
https://arxiv.org/abs/2508.12665

Multi-Granularity Distribution Modeling for Video Watch Time Prediction via Exponential-Gaussian Mixture Network
Accurate watch time prediction is crucial for enhancing user engagement in streaming short-video platforms, although it is challenged by complex distribution characteristics across multi-granularity levels. Through systematic analysis of real-world industrial data, we uncover two critical challenges in watch time prediction from a distribution aspect: (1) coarse-grained skewness induced by a significant concentration of quick-skips1, (2) fine-grained diversity arising from various user-video in…

GAP: Gaussianize Any Point Clouds with Text Guidance
Weiqi Zhang, Junsheng Zhou, Haotian Geng, Wenyuan Zhang, Yu-Shen Liu
https://arxiv.org/abs/2508.05631 https://

GAP: Gaussianize Any Point Clouds with Text Guidance
3D Gaussian Splatting (3DGS) has demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D representation, bridging the gap between point clouds and Gaussians becomes increasingly important. Recent studies have explored how to convert the colored points into Gaussians, but directly generating Gaussians from colorless 3D point clouds remains an unsolved challenge. In this paper, we propose GAP, a novel approa…

Supporting Software Formal Verification with Large Language Models: An Experimental Study
Weiqi Wang, Marie Farrell, Lucas C. Cordeiro, Liping Zhao
https://arxiv.org/abs/2507.04857

Supporting Software Formal Verification with Large Language Models: An Experimental Study
Formal methods have been employed for requirements verification for a long time. However, it is difficult to automatically derive properties from natural language requirements. SpecVerify addresses this challenge by integrating large language models (LLMs) with formal verification tools, providing a more flexible mechanism for expressing requirements. This framework combines Claude 3.5 Sonnet with the ESBMC verifier to form an automated workflow. Evaluated on nine cyber-physical systems from Lo…

On the Distribution of Age of Information in Time-varying Updating Systems
Jin Xu, Weiqi Wang, Natarajan Gautam
https://arxiv.org/abs/2507.03799 https://…

On the Distribution of Age of Information in Time-varying Updating Systems
Age of Information (AoI) is a crucial metric for quantifying information freshness in real-time systems where the sampling rate of data packets is time-varying. Evaluating AoI under such conditions is challenging, as system states become temporally correlated and traditional stationary analysis is inapplicable. We investigate an $M_{t}/G/1/1$ queueing system with a time-varying sampling rate and probabilistic preemption, proposing a novel analytical framework based on multi-dimensional partial …

Existence of normalized solutions to nonlinear Schr\"{o}dinger equations with potential on lattice graphs
Weiqi Guan
https://arxiv.org/abs/2507.04204 …

Existence of normalized solutions to nonlinear Schrödinger equations with potential on lattice graphs
We study the existence of ground state normalized solution of the following Schrödinger equation: \begin{equation*} \begin{cases} -Δu+V(x)u+λu=f(x,u), & x\in\mathbb{Z}^d \\ \Vert u\Vert_2^2=a \end{cases} \end{equation*} where $V(x)$ is trapping potential or well potential, $f(x,u)$ satisfies Berestycki-Lions type condition and other suitable conditions. We show that there always exists a threshold $α\in[0,\infty)$ such that there do not exist ground state normalized solutions for $a\in (0…

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving
Huanqi Hu, Bowen Xiao, Shixuan Sun, Jianian Yin, Zhexi Zhang, Xiang Luo, Chengquan Jiang, Weiqi Xu, Xiaoying Jia, Xin Liu, Minyi Guo
https://arxiv.org/abs/2509.01229

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving
Quantization is a critical technique for accelerating LLM inference by reducing memory footprint and improving computational efficiency. Among various schemes, 4-bit weight and 8-bit activation quantization (W4A8) offers a strong balance between accuracy and performance. However, existing W4A8 GEMM kernels fall short in practice due to inefficient dequantization on CUDA Cores, which cannot keep pace with the high throughput of Tensor Cores. In this paper, we present LiquidGEMM, a hardware-effic…

What Do Bouncing Balls Tell Us About the Universe? A Journey into Billiard Systems
Weiqi Chu, Matthew Dobson
https://arxiv.org/abs/2508.18519 https://arxiv…

What Do Bouncing Balls Tell Us About the Universe? A Journey into Billiard Systems
Have you ever played or watched a game of pool? If so, you have already seen a billiard system in action. In mathematics and physics, a billiard system describes a ball that moves in straight lines and bounces off walls. Despite these simple rules, billiard systems can produce remarkably rich behaviors: some table shapes generate regular, periodic patterns, while others give rise to complete chaos. Scientists also study what happens when we shrink the ball down to the size of an electron to a w…

Education-Oriented Graph Retrieval-Augmented Generation for Learning Path Recommendation
Xinghe Cheng, Zihan Zhang, Jiapu Wang, Liangda Fang, Chaobo He, Quanlong Guan, Shirui Pan, Weiqi Luo
https://arxiv.org/abs/2506.22303

Education-Oriented Graph Retrieval-Augmented Generation for Learning Path Recommendation
Learning path recommendation seeks to provide learners with a structured sequence of learning items (e.g., knowledge concepts or exercises) to optimize their learning efficiency. Despite significant efforts in this area, most existing methods primarily rely on prerequisite relationships, which present two major limitations: 1) Many educational datasets do not explicitly provide prerequisite relationships between knowledge concepts, hindering the application of current learning path recommendati…