Papers by Junyi Chai

3 papers
DeepGen: Diverse Search Ad Generation and Real-Time Customization (2022.emnlp-demos)

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Challenge: Existing systems that generate ads manually are not effective in generating ad copy and generating millions of ads for large businesses.
Approach: They propose a system that generates fluent ads from advertiser’s web pages in an abstractive fashion and solves practical issues such as factuality and inference speed.
Outcome: The proposed system generates fluent ads from advertiser’s web pages in an abstractive fashion and solves practical issues such as factuality and inference speed.
Automatic Construction of Enterprise Knowledge Base (2021.emnlp-demo)

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Challenge: Existing knowledge bases are often based on bootstrapping entities from human-curated sources such as Wikipedia.
Approach: They propose to build a knowledge base from enterprise documents with minimal human intervention by using deep learning models and classical machine learning techniques.
Outcome: The proposed system is currently serving as part of a Microsoft 365 service.
VEG: Verbal 𝜖-greedy for Semantic Exploration in Multi-Turn RL Agents (2026.acl-industry)

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Challenge: Standard RL approaches suffer from reward sparsity and mode-seeking behavior . lack of diversity hinders exploration necessary for optimal learning .
Approach: They propose a framework that leverages external feedback as a dynamic control variable to explicitly balance exploration and exploitation within the semantic space.
Outcome: Experiments on Tau Bench and SearchQA show that the proposed framework outperforms standard RL baselines.

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