activity
20242026
collaborators

5 papers

cs.CV2026

Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models

Ziyao Tang, Pengkun Jiao, Bin Zhu +3

Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under conversational interaction remains largely…

cs.LG2025

Dual-LoRA and Quality-Enhanced Pseudo Replay for Multimodal Continual Food Learning

Xinlan Wu, Bin Zhu, Feng Han +2

Food analysis has become increasingly critical for health-related tasks such as personalized nutrition and chronic disease prevention. However, existing large multimodal models (LM…

cs.AI2025

Don't Deceive Me: Mitigating Gaslighting through Attention Reallocation in LMMs

Pengkun Jiao, Bin Zhu, Jingjing Chen +2

Large Multimodal Models (LMMs) have demonstrated remarkable capabilities across a wide range of tasks. However, their vulnerability to user gaslighting-the deliberate use of mislea…

cs.CV2024

Domain Expansion and Boundary Growth for Open-Set Single-Source Domain Generalization

Pengkun Jiao, Na Zhao, Jingjing Chen +1

Open-set single-source domain generalization aims to use a single-source domain to learn a robust model that can be generalized to unknown target domains with both domain shifts an…

cs.CV2024

From Holistic to Localized: Local Enhanced Adapters for Efficient Visual Instruction Fine-Tuning

Pengkun Jiao, Bin Zhu, Jingjing Chen +2

Efficient Visual Instruction Fine-Tuning (EVIT) seeks to adapt Multimodal Large Language Models (MLLMs) to downstream tasks with minimal computational overhead. However, as task di…