Papers by ShaoGuo Liu

2 papers
CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning (2022.naacl-industry)

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Challenge: a paper focuses on automatically generating the text of an ad to capture user interest for achieving higher click-through rate.
Approach: They propose a CTR-driven advertising text generation approach to generate ad texts based on user reviews.
Outcome: The proposed approach outperforms existing approaches on industrial datasets and on large-scale unpaired reviews.
GODBench: A Benchmark for Multimodal Large Language Models in Video Comment Art (2025.acl-long)

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Challenge: Existing benchmarks for video comment art are constrained by their limited modalities and insufficient categories, hindering creativity in video-based comment art creation.
Approach: They propose a benchmark that integrates video and text modalities to evaluate MLLMs’ abilities to compose video Comment art.
Outcome: The proposed framework integrates video and text modalities to evaluate MLLMs’ abilities to compose video comment art.

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