Papers by Yuntian Gu
FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score (2023.emnlp-main)
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| Challenge: | Existing methods for detecting out-of-distribution instances are empirical . state-of the-art methods for OOD detection are suboptimal since they only estimate in-distance density pout(x). |
| Approach: | They propose a method that measures the “OOD-ness” of a test case x through the likelihood ratio between out-distribution mathcal Pout and in-division mathcal Pin. |
| Outcome: | The proposed method improves existing methods on popular benchmarks and establishes a new SOTA on popular NLP benchmarks. |
How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs (2025.findings-acl)
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Guhao Feng, Kai Yang, Yuntian Gu, Xinyue Ai, Shengjie Luo, Jiacheng Sun, Di He, Zhenguo Li, Liwei Wang
| Challenge: | Despite the success of transformer-based large language models, understanding and enhancing their mathematical capabilities remains a significant challenge. |
| Approach: | They propose to use numerical precision as a key factor that influences LLMs' effectiveness in arithmetical tasks to determine their effectiveness. |
| Outcome: | The proposed models perform better in arithmetic tasks than transformer-based models with standard numerical precision. |