4 citations · 4 across the 7 of their papers we have counts for
5 papers · 1 filter
Reasoning Guided Embeddings: Leveraging MLLM Reasoning for Improved Multimodal Retrieval
Chunxu Liu, Jiyuan Yang, Ruopeng Gao +4
Multimodal embeddings are widely used in downstream tasks such as multimodal retrieval, enabling alignment of interleaved modalities in a shared representation space. While recent…
FreeRet: MLLMs as Training-Free Retrievers
Yuhan Zhu, Xiangyu Zeng, Chenting Wang +6
Multimodal large language models (MLLMs) are emerging as versatile foundations for mixed-modality retrieval. Yet, they often require heavy post-hoc training to convert them into co…
SORCE: Small Object Retrieval in Complex Environments
Chunxu Liu, Chi Xie, Xiaxu Chen +4
Text-to-Image Retrieval (T2IR) is a highly valuable task that aims to match a given textual query to images in a gallery. Existing benchmarks primarily focus on textual queries des…
On the Suitability of Reinforcement Fine-Tuning to Visual Tasks
Xiaxu Chen, Wei Li, Chunxu Liu +5
Reinforcement Fine-Tuning (RFT) is proved to be greatly valuable for enhancing the reasoning ability of LLMs. Researchers have been starting to apply RFT to MLLMs, hoping it will a…
History-Aware Transformation of ReID Features for Multiple Object Tracking
Ruopeng Gao, Yuyao Wang, Chunxu Liu +1
In Multiple Object Tracking (MOT), Re-identification (ReID) features are widely employed as a powerful cue for object association. However, they are often wielded as a one-size-fit…