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20232026
most citedTarget-Guided Composed Image Retrieval

53 citations · 119 across the 20 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024★ 1 cited

Vision-guided and Mask-enhanced Adaptive Denoising for Prompt-based Image Editing

Kejie Wang, Xuemeng Song, Meng Liu +2

Text-to-image diffusion models have demonstrated remarkable progress in synthesizing high-quality images from text prompts, which boosts researches on prompt-based image editing th…

cs.LG2024

GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching

Xiao Han, Zijian Zhang, Xiangyu Zhao +6

As urban residents demand higher travel quality, vehicle dispatch has become a critical component of online ride-hailing services. However, current vehicle dispatch systems struggl…

cs.MM2024★ 30 cited

Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image Retrieval

Haokun Wen, Xuemeng Song, Xiaolin Chen +3

Composed image retrieval (CIR) aims to retrieve the target image based on a multimodal query, i.e., a reference image paired with corresponding modification text. Recent CIR studie…

cs.IR2024

MMGRec: Multimodal Generative Recommendation with Transformer Model

Han Liu, Yinwei Wei, Xuemeng Song +3

Multimodal recommendation aims to recommend user-preferred candidates based on her/his historically interacted items and associated multimodal information. Previous studies commonl…

cs.CV2024

Interactive Garment Recommendation with User in the Loop

Federico Becattini, Xiaolin Chen, Andrea Puccia +4

Recommending fashion items often leverages rich user profiles and makes targeted suggestions based on past history and previous purchases. In this paper, we work under the assumpti…

cs.CL2024★ 1 cited

Sentiment-enhanced Graph-based Sarcasm Explanation in Dialogue

Kun Ouyang, Liqiang Jing, Xuemeng Song +3

Sarcasm Explanation in Dialogue (SED) is a new yet challenging task, which aims to generate a natural language explanation for the given sarcastic dialogue that involves multiple m…