Papers by Naiqiang Tan

2 papers
D-Artemis: A Deliberative Cognitive Framework for Mobile GUI Multi-Agents (2026.findings-acl)

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Challenge: Graphical User Interface (GUI) agents aim to automate a wide spectrum of human tasks by emulating user interaction.
Approach: They propose a deliberative framework that leverages a fine-grained tip retrieval mechanism to inform its decision-making process.
Outcome: The proposed framework achieves SOTA among open-source general models on AndroidWorld and ScreenSpot-V2 . it leverages a fine-grained, app-specific tip retrieval mechanism to inform its decision-making process .
O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning (2026.findings-acl)

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Challenge: Recent long-thought reasoning models adopt extended reasoning processes similar to how humans ponder over complex problems.
Approach: They propose a model that uses RL-style fine-tuning to reduce inference overhead while maintaining accuracy.
Outcome: The proposed model reduces inference overhead while maintaining accuracy.

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