8 citations · 9 across the 6 of their papers we have counts for
7 papers
MIRAGE: Assessing Hallucination in Multimodal Reasoning Chains of MLLM
Bowen Dong, Minheng Ni, Zitong Huang +3
Multimodal hallucination in multimodal large language models (MLLMs) restricts the correctness of MLLMs. However, multimodal hallucinations are multi-sourced and arise from diverse…
MR-GDINO: Efficient Open-World Continual Object Detection
Bowen Dong, Zitong Huang, Guanglei Yang +2
Open-world (OW) recognition and detection models show strong zero- and few-shot adaptation abilities, inspiring their use as initializations in continual learning methods to improv…
Class Balance Matters to Active Class-Incremental Learning
Zitong Huang, Ze Chen, Yuanze Li +6
Few-Shot Class-Incremental Learning has shown remarkable efficacy in efficient learning new concepts with limited annotations. Nevertheless, the heuristic few-shot annotations may…
LPT++: Efficient Training on Mixture of Long-tailed Experts
Bowen Dong, Pan Zhou, Wangmeng Zuo
We introduce LPT++, a comprehensive framework for long-tailed classification that combines parameter-efficient fine-tuning (PEFT) with a learnable model ensemble. LPT++ enhances fr…
IMWA: Iterative Model Weight Averaging Benefits Class-Imbalanced Learning Tasks
Zitong Huang, Ze Chen, Bowen Dong +3
Model Weight Averaging (MWA) is a technique that seeks to enhance model's performance by averaging the weights of multiple trained models. This paper first empirically finds that 1…
ConSept: Continual Semantic Segmentation via Adapter-based Vision Transformer
Bowen Dong, Guanglei Yang, Wangmeng Zuo +1
In this paper, we delve into the realm of vision transformers for continual semantic segmentation, a problem that has not been sufficiently explored in previous literature. Empiric…
SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models
Lijun Li, Bowen Dong, Ruohui Wang +5
In the rapidly evolving landscape of Large Language Models (LLMs), ensuring robust safety measures is paramount. To meet this crucial need, we propose \emph{SALAD-Bench}, a safety…