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Researcher profile

Bing Han

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. How AI chatbots have reshaped the frontline interface in China: examining the role of sales–service ambidexterity and the personalization–privacy paradox

    2022 · International Journal of Emerging Markets

    Purpose This study serves two purposes: (1) to evaluate the effects of organizational ambidexterity by examining how the balanced and the combined sales–service configurations of chatbots differ in their abilities to enhance customer experience and …

  2. Semi-Supervised Clustering with Contrastive Learning for Discovering New Intents

    2022 · arXiv (Cornell University)

    Most dialogue systems in real world rely on predefined intents and answers for QA service, so discovering potential intents from large corpus previously is really important for building such dialogue services. Considering that most scenarios …

  3. Self-Supervised Speaker Verification Using Dynamic Loss-Gate and Label Correction

    2022 · arXiv (Cornell University)

    For self-supervised speaker verification, the quality of pseudo labels decides the upper bound of the system due to the massive unreliable labels. In this work, we propose dynamic loss-gate and label correction (DLG-LC) to alleviate …

  4. Exploring Binary Classification Loss For Speaker Verification

    2023 · arXiv (Cornell University)

    The mismatch between close-set training and open-set testing usually leads to significant performance degradation for speaker verification task. For existing loss functions, metric learning-based objectives depend strongly on searching effective pairs which might hinder further …

  5. Hierarchical Prompt Tuning for Few-Shot Multi-Task Learning

    2023

    Prompt tuning has enhanced the performance of Pre-trained Language Models for multi-task learning in few-shot scenarios. However, existing studies fail to consider that the prompts among different layers in Transformer are different due to the …

  6. Integrating Large Language Models with Graphical Session-Based Recommendation

    2024 · arXiv (Cornell University)

    With the rapid development of Large Language Models (LLMs), various explorations have arisen to utilize LLMs capability of context understanding on recommender systems. While pioneering strategies have primarily transformed traditional recommendation tasks into challenges of …