Xi Chen

ARCHE: A Novel Task to Evaluate LLMs on Latent Reasoning Chain Extraction

Pengze Li, Jiaqi Liu, Junchi Yu, Lihao Liu et autres

Large language models (LLMs) are increasingly used in scientific domains. While they can produce reasoning-like content via methods such as chain-of-thought prompting, these outputs are typically unstructured and informal, obscuring whether models truly understand the fundamental reasoning paradigms that underpin scientific inference. …

U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMs

Xiaojie Li, Chu Li, Shizhe Chen, Xi Chen

Universal multimodal retrieval (UMR), which aims to address complex retrieval tasks where both queries and candidates span diverse modalities, has been significantly advanced by the emergence of MLLMs. While state-of-the-art MLLM-based methods in the literature predominantly adopt contrastive learning principles, they often …

PH-VAE: A Polynomial Hierarchical Variational Autoencoder Towards Disentangled Representation Learning

Xi Chen, Shaofan Li

The variational autoencoder (VAE) is a simple and efficient generative artificial intelligence method for modeling complex probability distributions of various types of data, such as images and texts. However, it suffers some main shortcomings, such as lack of interpretability in the latent …

Enhancing Multi-Category Smoke Detection Using Similarity Constrained Loss

Xi Chen

Smoke detection plays a crucial role in ensuring public safety across various domains, including industrial settings, daily life, and disaster management. The effectiveness of smoke detection models heavily relies on the availability of comprehensive datasets and the optimization of loss functions. However, …

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Self-Refined Generative Foundation Models for Wireless Traffic Prediction

Chengming Hu, Hao Zhou, Di Wu, Xi Chen et autres

With a broad range of emerging applications in 6G networks, wireless traffic prediction has become a critical component of network management. However, the dynamically shifting distribution of wireless traffic in non-stationary 6G networks presents significant challenges to achieving accurate and stable predictions. …

Adversarial defence by learning differentiated feature representation in deep ensemble

Xi Chen, Wei Huang, Wei Guo, Fan Zhang et autres

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Correction: Adversarial defence by learning differentiated feature representation in deep ensemble

Xi Chen, Wei Huang, Wei Guo, Fan Zhang et autres

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Diversity supporting robustness: Enhancing adversarial robustness via differentiated ensemble predictions

Xi Chen, Wei Huang, Ziwen Peng, Fan Zhang

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Research progress of micro precision machine tool

Xi Chen, Li Sun, Wei Huang, Pinlei Lv et autres

Welcome to the WIT Press eLibrary - the home of the Transactions of the Wessex Institute collection, providing on-line access to papers presented at the Institute's prestigious international conferences and from its State-of-the-Art in Science & Engineering publications.

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