Chen Zhang
13 papers in the PaperMetrix corpus
Papers by this author
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Syntax-Aware Aspect-Level Sentiment Classification with Proximity-Weighted Convolution Network
2019
It has been widely accepted that Long Short-Term Memory (LSTM) network, coupled with attention mechanism and memory module, is useful for aspect-level sentiment classification. However, existing approaches largely rely on the modelling of semantic relatedness …
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Research and Application of Artificial Neural Network Technology in the Recognition Model of Employee Satisfaction
2021 · 2021 International Conference on Aviation Safety and Information Technology
In a highly competitive industry, the phenomenon of brain drain is even more prominent. Many industries recognize the role of talents in the development of the industry. Attracting and retaining outstanding talents should improve employee …
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Variational quantum circuit learning of entanglement purification in multiple degrees of freedom
2022 · arXiv (Cornell University)
Entanglement purification is a crucial technique for promising the effective entanglement channel in noisy large-scale quantum networks, yet complicated in designing protocols in multi-degree of freedom (DoF). To execute the above tasks easily and effectively, …
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XPrompt: Exploring the Extreme of Prompt Tuning
2022
Prompt tuning learns soft prompts to condition the frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gradually reached the performance level of fine-tuning as the model …
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Oblivion: Poisoning Federated Learning by Inducing Catastrophic Forgetting
2023
Federated learning is exposed to model poisoning attacks as compromised clients may submit malicious model updates to pollute the global model. To defend against such attacks, robust aggregation rules are designed for the centralized server …
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Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection
2023 · arXiv (Cornell University)
While large language models (LLMs) such as ChatGPT and PaLM have demonstrated remarkable performance in various language understanding and generation tasks, their capabilities in complex reasoning and intricate knowledge utilization still fall short of human-level …
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Resource Management Based on Resource Parameters in Computing Networks
2024
In computing networks, the management center quickly schedules storage and computing resources of cloud-edge-device heterogeneous system. As the complexity of the network increases and resource nodes continue to be accessed, the burden on management center …
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RefXVC: Cross-Lingual Voice Conversion With Enhanced Reference Leveraging
2024 · IEEE/ACM Transactions on Audio Speech and Language Processing
This paper proposes RefXVC, a method for cross-lingual voice conversion (XVC) that leverages reference information to improve conversion performance. Previous XVC works generally take an average speaker embedding to condition the speaker identity, which does …
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Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language Models
2025
Haoyang Li, Xuejia Chen, Zhanchao Xu, Darian Li, Nicole Hu, Fei Teng, Yiming Li, Luyu Qiu, Chen Jason Zhang, Li Qing, Lei Chen. Findings of the Association for Computational Linguistics: ACL 2025. 2025.
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Towards the Law of Capacity Gap in Distilling Language Models
2025
Language model (LM) distillation aims at distilling the knowledge in a large teacher LM to a small student one. As a critical issue facing LM distillation, a superior student often arises from a teacher of …
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From Human Memory to AI Memory: A Survey on Memory Mechanisms in the Era of LLMs
2025 · arXiv (Cornell University)
Memory is the process of encoding, storing, and retrieving information, allowing humans to retain experiences, knowledge, skills, and facts over time, and serving as the foundation for growth and effective interaction with the world. It …
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AXIS: Explainable Time Series Anomaly Detection with Large Language Models
2025 · arXiv (Cornell University)
Time-series anomaly detection (TSAD) increasingly demands explanations that articulate not only if an anomaly occurred, but also what pattern it exhibits and why it is anomalous. Leveraging the impressive explanatory capabilities of Large Language Models …
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Towards Flow-Matching-based TTS without Classifier-Free Guidance
2025 · arXiv (Cornell University)
Flow matching has demonstrated strong generative capabilities and has become a core component in modern Text-to-Speech (TTS) systems. To ensure high-quality speech synthesis, Classifier-Free Guidance (CFG) is widely used during the inference of flow-matching-based TTS …