Papers with statistical uncertainty
Statistical Uncertainty in Word Embeddings: GloVe-V (2024.emnlp-main)
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| Challenge: | Static word embeddings are ubiquitous in computational social science applications . however, assessing the statistical uncertainty in downstream conclusions remains challenging . |
| Approach: | They propose a method to obtain approximate, easy-to-use, and scalable reconstruction error variance estimates for one of the most widely used word embedding models. |
| Outcome: | The proposed method enables hypothesis testing in key word embedding tasks. |
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control (2025.findings-acl)
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Liu Huanshuo, Hao Zhang, Zhijiang Guo, Jing Wang, Kuicai Dong, Xiangyang Li, Yi Quan Lee, Cong Zhang, Yong Liu
| Challenge: | Existing methods focus on detecting LLM’s confidence via statistical uncertainty. |
| Approach: | They propose to use a representation perspective to solve adaptive RAG by enabling dynamic retrieval during generation and enabling retrieval only when the query exceeds LLM's internal knowledge. |
| Outcome: | The proposed framework is superior to existing adaptive RAG methods on a diverse set of tasks. |
Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress? (2024.emnlp-main)
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| Challenge: | Several studies claim that domain-adaptive pretraining improves performance on downstream medical tasks. |
| Approach: | They compare medical LLMs and VLMs against their corresponding base models . they find that medical Lms outperform their base models in 12.1% of cases . |
| Outcome: | The proposed models outperform their base models on medical questions and tasks in 12.1% of cases and reach a tie in 49.8% of cases. |