8 papers
On the Robustness of Machine Unlearning for Vision-Language Models
Yujie Lin, Kaidi Jia, Jiayao Ma +2
Vision-language models (VLMs) may memorize undesirable information from training data, motivating growing interest in machine unlearning. In this work, we present the first systema…
Object Hallucination-Free Reinforcement Unlearning for Vision-Language Models
Kaidi Jia, Yujie Lin, Chengyi Yang +2
Vision-language models (VLMs) raise growing concerns about privacy, copyright, and bias, motivating machine unlearning to remove sensitive knowledge. However, existing methods prim…
RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks
Ruiying Li, Yunlang Zhou, YuYao Zhu +15
Vision-Language-Action (VLA) systems have shown strong potential for language-driven robotic manipulation. However, scaling them to long-horizon tasks remains challenging. Existing…
ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation
Yuzhe Shang, Pengzhi Gao, Yazheng Yang +4
Large language models (LLMs) have recently demonstrated promising performance in simultaneous machine translation (SimulMT). However, applying decoder-only LLMs to SimulMT introduc…
BioPro: Towards Difference-Aware Gender Fairness for Vision-Language Models
Yujie Lin, Jiayao Ma, Qingguo Hu +4
Vision-Language Models (VLMs) inherit significant social biases from their training data, notably in gender representation. Current fairness interventions often adopt a difference-…
Text-based Aerial-Ground Person Retrieval
Xinyu Zhou, Yu Wu, Jiayao Ma +3
This work introduces Text-based Aerial-Ground Person Retrieval (TAG-PR), which aims to retrieve person images from heterogeneous aerial and ground views with textual descriptions.…
Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance
Wenhao Wang, Jianheng Song, Chiming Liu +13
While Vision-Language-Action (VLA) models show strong generalizability in various tasks, real-world deployment of robotic policy still requires large-scale, high-quality human expe…
Multimodal Large Language Models for Text-rich Image Understanding: A Comprehensive Review
Pei Fu, Tongkun Guan, Zining Wang +8
The recent emergence of Multi-modal Large Language Models (MLLMs) has introduced a new dimension to the Text-rich Image Understanding (TIU) field, with models demonstrating impress…