Papers by Wenchao Meng

2 papers
LearnAct: Few-Shot Mobile GUI Agent with a Unified Demonstration Benchmark (2026.findings-acl)

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Challenge: Mobile GUI agents show promise in automating tasks but face significant generalization challenges in long-tail scenarios.
Approach: They propose a benchmark framework for mobile GUI agents that measures the performance of GUI agents by analyzing their performance.
Outcome: The LearnGUI benchmark outperforms existing methods in offline and online evaluations and demonstrates consistent gains across model architectures.
Markovian Linguistic-Temporal Bridge: Unlocking the Potential of LLMs for Time Series Forecasting (2026.acl-long)

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Challenge: Pretrained Large Language Models (LLMs) are based on token-level linguistic-temporal alignment, leading to stacking of logically disjointed tokens as input.
Approach: They propose a framework that distills latent evolutionary patterns of language into a Markovian state transition graph, which is transferred as a structural prior to the time series domain.
Outcome: The proposed framework achieves global structural isomorphism between the linguistic and temporal domains.

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