arXiv subjects

Zhiwei Zhu

Publications and source records attributed to Zhiwei Zhu.

9 recordsLinked to original sources

arXiv2026

RT-Counter: Real-Time Text-Guided Open-Vocabulary Object Counting

Text-guided open-vocabulary object counting (TOOC) aims to count objects belonging to the categories specified by natural language descriptions. Although vision-language pre-trained models have been successful applied to TOOC tasks, they still struggle with fine-grained spatial understanding and real-time inference requirements in counting scenarios. To address these limitations, this paper proposes a real-time TOOC framework, called the Real-Time Counter (RT-Counter), that achieves not only good counting accuracy but also high computational efficiency. RT-Counter designs a novel Visual Prototype Textualization (VPT) module that can project learned visual features into a text feature space and then generate features containing the abstract information that is hard to capture with visual prototypes and the detailed prototype information that is difficult to describe in text, enhancing the object-level visual-language model's counting capabilities. Additionally, RT-Counter incorporates our Weaving Transformer (Weaformer) layers, maintaining high descriptive power at a fraction of the computational cost. The Weaformer layer adopts a novel hybrid attention mechanism that can efficiently weave together local and global visual features. Extensive experiments on three public datasets show that RT-Counter successfully breaks the accuracy-speed trade-off in TOOC. While achieving a competitive MAE of 13.30 on FSC147, RT-Counter operates at 112.48 FPS, making it 7.4x faster and over 4$\times$ more parameter-efficient than the existing leading methods in TOOC. Our work aims at balancing high accuracy and real-time performance in TOOC. Code is available at: https://github.com/Jason-Mar1/RT-Counter.

cs.CV↗

arXiv2026

Vehicle-Mounted Mid-Infrared Dual-Comb Spectroscopy for On-Road Trace Gas Detection

Advances in mid-infrared (MIR) dual-comb spectroscopy (DCS) have significantly enhanced molecular detection in recent years. The capability of DCS to precisely identify and quantify atmospheric trace gases makes it attractive for field applications across the environmental, agricultural, energy, and industrial sectors. In particular, there is a growing demand for mobile and continuous gas monitoring in outdoor environments where emission sources and sinks are often episodic and spatially heterogeneous. However, the practical field-deployment of DCS on mobile platforms under realistic field conditions has remained limited. This study demonstrates for the first time a vehicle-mounted MIR DCS system that enables continuous mobile atmospheric sampling across multiple outdoor sites and road environments. The system exhibited a stable signal-to-noise performance during on-road operation, including expressway driving at speeds up to 100 km/h. Furthermore, natural-gas leakage sources were successfully located and a two-dimensional methane concentration field was reconstructed around a controlled release source. In the future, the system can be integrated into more mobile platforms, such as unmanned aerial vehicles, enabling flexible trace gas detection over urban-scale regions.

physics.optics↗

arXiv2025

Extriangulated factorization systems, $s$-torsion pairs and recollements

We introduce extriangulated factorization systems in extriangulated categories and show that there exists a bijection between $s$-torsion pairs and extriangulated factorization systems. We also consider the gluing of $s$-torsion pairs and extriangulated factorization systems under recollements of extriangulated categories.

math.CT↗

arXiv2025

ComRAG: Retrieval-Augmented Generation with Dynamic Vector Stores for Real-time Community Question Answering in Industry

Community Question Answering (CQA) platforms can be deemed as important knowledge bases in community, but effectively leveraging historical interactions and domain knowledge in real-time remains a challenge. Existing methods often underutilize external knowledge, fail to incorporate dynamic historical QA context, or lack memory mechanisms suited for industrial deployment. We propose ComRAG, a retrieval-augmented generation framework for real-time industrial CQA that integrates static knowledge with dynamic historical QA pairs via a centroid-based memory mechanism designed for retrieval, generation, and efficient storage. Evaluated on three industrial CQA datasets, ComRAG consistently outperforms all baselines--achieving up to 25.9% improvement in vector similarity, reducing latency by 8.7% to 23.3%, and lowering chunk growth from 20.23% to 2.06% over iterations.

cs.CL↗

arXiv2025

Wakamatsu-tilting subcategories in extriangulated categories

Let $\mathscr{C}$ be an extriangulated category with enough projectives and injectives. We give the definitions of Wakamatsu-tilting subcategories and Wakamatsu-cotilting subcategories of $\mathscr{C}$ and show that they coincide with each other. Moreover, the definitions of $\infty$-tilting subcategories and $\infty$-cotilting subcategories given by Zhang, Wei and Wang also coincide with them. As a result, Wakamatsu-tilting subcategories success all properties of $\infty$-tilting subcategories and $\infty$-cotilting subcategories. On the other hand, we glue the Wakamatsu-tilting subcategories in a special recollement and show that the converse of the gluing holds under certain conditions.

math.RT↗

arXiv2024

A bijection between support $τ$-tilting subcategories and $τ$-cotorsion pairs in extriangulated categories

Let $\mathscr{C}$ be an extriangulated category with enough projectives and injectives. We give a new definition of tilting subcategories of $\mathscr{C}$ and prove it coincides with the definition given in [19]. As applications, we introduce the notions of support $τ$-tilting subcategories and $τ$-cotorsion pairs of $\mathscr{C}$. We build a bijection between support $τ$-tilting subcategories and certain $τ$-cotorsion pairs. Moreover, this bijection induces a bijection between tilting subcategories and certain cotorsion pairs.

math.RT↗

arXiv2024

A Note on Odd Periodic derived Hall algebras

Let $m$ be an odd positive integer and $D_m(\mathcal {A})$ be the $m$-periodic derived category of a finitary hereditary abelian category $\mathcal {A}$. In this note, we prove that there is an embedding of algebras from the derived Hall algebra of $D_m(\mathcal {A})$ defined by Xu-Chen [13] to the extended derived Hall algebra of $D_m(\mathcal {A})$ defined in [16]. This homomorphism is given on basis elements, rather than just on generating elements.

math.RT↗

arXiv2023

BotHawk: An Approach for Bots Detection in Open Source Software Projects

Social coding platforms have revolutionized collaboration in software development, leading to using software bots for streamlining operations. However, The presence of open-source software (OSS) bots gives rise to problems including impersonation, spamming, bias, and security risks. Identifying bot accounts and behavior is a challenging task in the OSS project. This research aims to investigate bots' behavior in open-source software projects and identify bot accounts with maximum possible accuracy. Our team gathered a dataset of 19,779 accounts that meet standardized criteria to enable future research on bots in open-source projects. We follow a rigorous workflow to ensure that the data we collect is accurate, generalizable, scalable, and up-to-date. We've identified four types of bot accounts in open-source software projects by analyzing their behavior across 17 features in 5 dimensions. Our team created BotHawk, a highly effective model for detecting bots in open-source software projects. It outperforms other models, achieving an AUC of 0.947 and an F1-score of 0.89. BotHawk can detect a wider variety of bots, including CI/CD and scanning bots. Furthermore, we find that the number of followers, number of repositories, and tags contain the most relevant features to identify the account type.

cs.SE↗

arXiv2021

On ductile-regime elliptical vibration cutting of silicon with identifying the lower bound of practical nominal cutting velocity

This study investigates the ductile-to-brittle transition behavior in elliptical vibration cutting (EVC) of silicon and identifies the practical process window for ductile-regime cutting. EVC has been reported to increase the critical depth of ductile-regime cutting of silicon. This study demonstrates that the enhanced ductile cutting performance, however, is only optimal in a carefully-determined process window. The vibration amplitudes and nominal cutting velocity have significant impacts on the ductile-to-brittle transition behaviors. Systematic experiments covering a wide span of vibration amplitudes and cutting velocity have been conducted to investigate their effects. Two quantitative performance indices, the critical depth and ductile ratio, are utilized to analyze cutting performance by considering two unique characteristics of elliptical vibration cutting, i.e., the time-varying undeformed chip thickness and effective cutting direction angle. The results show that there exists a lower bound for the nominal cutting velocity to ensure the ductile-regime material removal, besides the well-known upper bound. Besides, the increases of vibration amplitudes in both the cutting and depth-of-cut (DOC) directions first enhance but then deteriorate the cutting performance. Based on the theoretical analysis and experimental results, the optimal process parameters have been recommended for the elliptical vibration cutting of silicon.

physics.app-ph↗