82 citations · 83 across the 13 of their papers we have counts for
7 papers · 1 filter
Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs
Zhixiao Zheng, Zheren Fu, Zhiyuan Yao +3
Despite the rapid progress of Multimodal Large Language Models (MLLMs), they still suffer from untruthfulness issues, such as visual hallucinations, content fabrication, and unfait…
Learning to Compose: Revisiting Proxy Task Design for Zero-Shot Composed Image Retrieval
Jingjing Zhang, Lei Zhang, Zheren Fu +1
Composed Image Retrieval (CIR) retrieves a target image from a reference image and a textual modification. While supervised CIR relies on costly triplets, Zero-Shot CIR (ZS-CIR) al…
ADAPT: Attention Dynamics Alignment with Preference Tuning for Faithful MLLMs
Zhiyuan Yao, Zheren Fu, Zhixiao Zheng +3
Multimodal Large Language Models (MLLMs) are critically hampered by hallucination, generating content inconsistent with the provided image. In this paper, we identify an internal s…
Lance: Unified Multimodal Modeling by Multi-Task Synergy
Fengyi Fu, Mengqi Huang, Shaojin Wu +10
We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather than relying on model capacity…
Video-LevelGauge: Investigating Contextual Positional Bias in Large Video Language Models
Hou Xia, Zheren Fu, Fangcan Ling +4
Large video language models (LVLMs) have made notable progress in video understanding, spurring the development of corresponding evaluation benchmarks. However, existing benchmarks…
Qwen2.5-VL Technical Report
Shuai Bai, Keqin Chen, Xuejing Liu +24
We introduce Qwen2.5-VL, the latest flagship model of Qwen vision-language series, which demonstrates significant advancements in both foundational capabilities and innovative func…
Intra-class Adaptive Augmentation with Neighbor Correction for Deep Metric Learning
Zheren Fu, Zhendong Mao, Bo Hu +2
Deep metric learning aims to learn an embedding space, where semantically similar samples are close together and dissimilar ones are repelled against. To explore more hard and info…