Papers by Junyan Cheng

2 papers
Multimodal Phased Transformer for Sentiment Analysis (2021.emnlp-main)

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Challenge: Existing methods to model multimodal sentiment analysis are limited due to their complexity and memory footprint.
Approach: They propose a multimodal Sparse Phased Transformer to reduce self-attention complexity and memory footprint.
Outcome: The proposed method achieves comparable or superior performance with a 90% reduction in the number of parameters.
Apeiron: A Scalable LLM-agentic Framework for Autonomous Full-lifecycle Demand-optimized Application Synthesis (2026.findings-acl)

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Challenge: Traditional, rigid, 'one-size-fits-all' apps are struggling in the contemporary landscape.
Approach: They propose a scalable and extensible framework for addressing *amorphous* user demands through autonomous, full-lifecycle application synthesis.
Outcome: The proposed framework outperforms baselines in CUA ratings and user-demand task scores across 300 app scenarios, 2,400 personas, and 46,338 demands.

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