Papers by Jianfeng Wen

2 papers
VENUS: A VLLM-driven Video Content Discovery System for Real Application Scenarios (2025.emnlp-industry)

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Challenge: Video Content Discovery (VCD) is to identify specific videos defined by a pre-specified text policy.
Approach: They propose a Vision-Language Large Model-driven video content discovery system called VENUS to solve these problems.
Outcome: The proposed system generates high-quality, VCD-specific data for model training and extends it to support it better.
Implicit Deep Latent Variable Models for Text Generation (D19-1)

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Challenge: Variational auto-encoders have been used for text generation but their representation power is limited due to two reasons.
Approach: They advocate sample-based representations of variational distributions for natural language . they further develop an LVM to directly match the aggregated posterior to the prior .
Outcome: The proposed model can be viewed as a natural extension of VAEs with a regularization of maximizing mutual information, mitigating the "posterior collapse" issue.

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