Papers by Guoheng Sun

2 papers
Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL (2026.findings-acl)

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Challenge: Translating natural language questions into SQL is a core challenge in natural language understanding and human-computer interaction.
Approach: They propose a reinforcement learning framework and model family to generate accurate, executable SQL using a lightweight reward signal based solely on execution correctness.
Outcome: The proposed framework outperforms previous versions of 70B-class systems and achieves state-of-the-art execution accuracy across six diverse Text2SQL benchmarks.
Router-Tuning: A Simple and Effective Approach for Dynamic Depth (2025.emnlp-main)

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Challenge: Existing methods to improve computational efficiency are under-explored and face several critical challenges.
Approach: They propose a method that selectively activates only a subset of the model's layers, skipping those deemed less important.
Outcome: The proposed method significantly improves performance on Attention layers and MoE layers while reducing redundant computation and memory usage.

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