20 citations · 77 across the 19 of their papers we have counts for
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cs.AI2025
Shapley Uncertainty in Natural Language Generation
Meilin Zhu, Gaojie Jin, Xiaowei Huang +1
In question-answering tasks, determining when to trust the outputs is crucial to the alignment of large language models (LLMs). Kuhn et al. (2023) introduces semantic entropy as a…
cs.AI2023
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models
Liang Zhang, Nathaniel Xu, Pengfei Yang +3
Robust pedestrian trajectory forecasting is crucial to developing safe autonomous vehicles. Although previous works have studied adversarial robustness in the context of trajectory…
cs.AI2023★ 17 cited
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
Xiaowei Huang, Wenjie Ruan, Wei Huang +14
Large Language Models (LLMs) have exploded a new heatwave of AI for their ability to engage end-users in human-level conversations with detailed and articulate answers across many…