6 papers · 1 filter
DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
Jingyu Song, Zhenxin Li, Shiyi Lan +6
Benchmarking autonomous driving planners to align with human judgment remains a critical challenge, as state-of-the-art metrics like the Extended Predictive Driver Model Score (EPD…
Mitigating Multimodal Hallucinations via Gradient-based Self-Reflection
Shan Wang, Maying Shen, Nadine Chang +3
Multimodal large language models achieve strong performance across diverse tasks but remain prone to hallucinations, where outputs are not grounded in visual inputs. This issue can…
MDP: Multidimensional Vision Model Pruning with Latency Constraint
Xinglong Sun, Barath Lakshmanan, Maying Shen +3
Current structural pruning methods face two significant limitations: (i) they often limit pruning to finer-grained levels like channels, making aggressive parameter reduction chall…
Global Average Feature Augmentation for Robust Semantic Segmentation with Transformers
Alberto Gonzalo Rodriguez Salgado, Maying Shen, Philipp Harzig +2
Robustness to out-of-distribution data is crucial for deploying modern neural networks. Recently, Vision Transformers, such as SegFormer for semantic segmentation, have shown impre…
SSE: Multimodal Semantic Data Selection and Enrichment for Industrial-scale Data Assimilation
Maying Shen, Nadine Chang, Sifei Liu +1
In recent years, the data collected for artificial intelligence has grown to an unmanageable amount. Particularly within industrial applications, such as autonomous vehicles, model…
Step Out and Seek Around: On Warm-Start Training with Incremental Data
Maying Shen, Hongxu Yin, Pavlo Molchanov +2
Data often arrives in sequence over time in real-world deep learning applications such as autonomous driving. When new training data is available, training the model from scratch u…