Papers by Qianyu Feng

2 papers
Uncovering Limitations in Text-to-Image Generation: A Contrastive Approach with Structured Semantic Alignment (2023.findings-emnlp)

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Challenge: a new method for text-to-image generation models is proposed to address these limitations . SSA focuses on learning structured semantic embeddings across different modalities .
Approach: They propose a method to evaluate text-to-image generation models using structured semantic embeddings . they propose to learn mutated prompts by substituting words with equivalent or nonequivalent alternatives .
Outcome: The proposed method improves the measurement of semantic consistency of text-to-image generation models.
Mastering the Craft of Data Synthesis for CodeLLMs (2025.naacl-long)

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Challenge: Large language models (LLMs) have shown impressive performance in code understanding and generation.
Approach: They propose a systematic review of large language models and their taxonomy and propose specialized LLMs for code-related tasks.
Outcome: The proposed models have shown to be highly effective in coding tasks.

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