6 citations · 6 across the 6 of their papers we have counts for
10 papers
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…
Efficient Test-Time Retrieval Augmented Generation
Hailong Yin, Bin Zhu, Jingjing Chen +1
Although Large Language Models (LLMs) demonstrate significant capabilities, their reliance on parametric knowledge often leads to inaccuracies. Retrieval Augmented Generation (RAG)…
Benchmarking Gaslighting Negation Attacks Against Reasoning Models
Bin Zhu, Hailong Yin, Jingjing Chen +1
Recent advances in reasoning-centric models promise improved robustness through mechanisms such as chain-of-thought prompting and test-time scaling. However, their ability to withs…
Advancing Food Nutrition Estimation via Visual-Ingredient Feature Fusion
Huiyan Qi, Bin Zhu, Chong-Wah Ngo +2
Nutrition estimation is an important component of promoting healthy eating and mitigating diet-related health risks. Despite advances in tasks such as food classification and ingre…
Efficient Prompt Tuning for Hierarchical Ingredient Recognition
Yinxuan Gui, Bin Zhu, Jingjing Chen +1
Fine-grained ingredient recognition presents a significant challenge due to the diverse appearances of ingredients, resulting from different cutting and cooking methods. While exis…
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…