13 citations · 26 across the 14 of their papers we have counts for
17 papers
CMMaTH: A Chinese Multi-modal Math Skill Evaluation Benchmark for Foundation Models
Zhong-Zhi Li, Ming-Liang Zhang, Fei Yin +7
Due to the rapid advancements in multimodal large language models, evaluating their multimodal mathematical capabilities continues to receive wide attention. Despite the datasets l…
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models
Xiang Gao, Jiaxin Zhang, Lalla Mouatadid +1
In recent years, large language models (LLMs) have become increasingly prevalent, offering remarkable text generation capabilities. However, a pressing challenge is their tendency…
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods
Jiaxin Zhang, Kamalika Das, Sricharan Kumar
Uncertainty estimation is a crucial aspect of deploying dependable deep learning models in safety-critical systems. In this study, we introduce a novel and efficient method for det…
DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models
Wendi Cui, Jiaxin Zhang, Zhuohang Li +4
Evaluating the quality and variability of text generated by Large Language Models (LLMs) poses a significant, yet unresolved research challenge. Traditional evaluation methods, suc…
On the Quantification of Image Reconstruction Uncertainty without Training Data
Sirui Bi, Victor Fung, Jiaxin Zhang
Computational imaging plays a pivotal role in determining hidden information from sparse measurements. A robust inverse solver is crucial to fully characterize the uncertainty indu…
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
Jiaxin Zhang, Zhuohang Li, Kamalika Das +1
Large language models (LLMs) have demonstrated remarkable capabilities in various tasks. However, their suitability for domain-specific tasks, is limited due to their immense scale…