15 citations · 29 across the 9 of their papers we have counts for
9 papers
DSI-Bench: A Benchmark for Dynamic Spatial Intelligence
Ziang Zhang, Zehan Wang, Guanghao Zhang +5
Reasoning about dynamic spatial relationships is essential, as both observers and objects often move simultaneously. Although vision-language models (VLMs) and visual expertise mod…
APO: Enhancing Reasoning Ability of MLLMs via Asymmetric Policy Optimization
Minjie Hong, Zirun Guo, Yan Xia +4
Multimodal Large Language Models (MLLMs) are powerful at integrating diverse data, but they often struggle with complex reasoning. While Reinforcement learning (RL) can boost reaso…
Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval
Ruofan Hu, Yan Xia, Minjie Hong +5
Multimodal large language models (MLLMs) have seen substantial progress in recent years. However, their ability to represent multimodal information in the acoustic domain remains u…
EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration
Minjie Hong, Yan Xia, Zehan Wang +8
Large language models (LLMs) are increasingly leveraged as foundational backbones in the development of advanced recommender systems, offering enhanced capabilities through their e…
EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration
Ye Wang, Jiahao Xun, Minjie Hong +8
Generative retrieval has recently emerged as a promising approach to sequential recommendation, framing candidate item retrieval as an autoregressive sequence generation problem. H…
Enhancing Multimodal Unified Representations for Cross Modal Generalization
Hai Huang, Yan Xia, Shengpeng Ji +7
To enhance the interpretability of multimodal unified representations, many studies have focused on discrete unified representations. These efforts typically start with contrastive…
Multi-Modal Domain Adaptation Across Video Scenes for Temporal Video Grounding
Haifeng Huang, Yang Zhao, Zehan Wang +2
Temporal Video Grounding (TVG) aims to localize the temporal boundary of a specific segment in an untrimmed video based on a given language query. Since datasets in this domain are…
Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks
Haoyi Duan, Yan Xia, Mingze Zhou +3
In recent years, the deployment of large-scale pre-trained models in audio-visual downstream tasks has yielded remarkable outcomes. However, these models, primarily trained on sing…
Video-Guided Curriculum Learning for Spoken Video Grounding
Yan Xia, Zhou Zhao, Shangwei Ye +3
In this paper, we introduce a new task, spoken video grounding (SVG), which aims to localize the desired video fragments from spoken language descriptions. Compared with using text…