Papers by Xuefeng Su

2 papers
ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistants (2026.acl-long)

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Challenge: Existing studies on large language model-based agents focus on evaluation benchmarks without training support.
Approach: They propose a large-scale Chinese shopping simulation environment that uses large language models to train agents.
Outcome: The proposed model performs poorly in a large-scale and challenging shopping environment in China.
A Knowledge-Guided Framework for Frame Identification (2021.acl-long)

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Challenge: Existing frameworks for frame identification are limited to only a few types of frame knowledge.
Approach: They propose a Knowledge-Guided Frame Identification framework that integrates frame knowledge to learn better frame representation.
Outcome: The proposed framework outperforms the state-of-the-art methods on two benchmark datasets.

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