Papers by Chengru Song

2 papers
VidCapBench: A Comprehensive Benchmark of Video Captioning for Controllable Text-to-Video Generation (2025.findings-acl)

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Challenge: Existing studies have not identified a link between video caption evaluation and T2V generation.
Approach: They propose a video caption evaluation scheme specifically designed for T2V generation that integrates video annotation with caption evaluation.
Outcome: The proposed system is agnostic to any particular caption format and can be used for training.
Decoding at the Speed of Thought: Harnessing Parallel Decoding of Lexical Units for LLMs (2024.lrec-main)

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Challenge: Large language models have demonstrated exceptional capability in natural language understanding and generation, but their generation speed is limited by the inherently sequential nature of their decoding process.
Approach: They propose a method that accelerates decoding process without sacrificing quality . they propose lexical unit decoding, which can be integrated with other methods .
Outcome: The proposed method significantly reduces decoding time while maintaining quality while maintaining output quality.

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