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20242026
most citedAdaptive Patch Contrast for Weakly Supervised Semantic Segmentation

44 citations · 48 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2026

SQuaD-SQL: Efficient Text-to-SQL with Small Language Models via LLM-Guided Knowledge Distillation

Wangyu Wu, Xiaojian Lin, Rong Fu +4

Text-to-SQL is a fundamental task in natural language processing that enables users to interact with structured databases using natural language. While large language models (LLMs)…

cs.CV2025

SynthSeg-Agents: Multi-Agent Synthetic Data Generation for Zero-Shot Weakly Supervised Semantic Segmentation

Wangyu Wu, Zhenhong Chen, Xiaowei Huang +2

Weakly Supervised Semantic Segmentation (WSSS) with image level labels aims to produce pixel level predictions without requiring dense annotations. While recent approaches have lev…

cs.CV2025★ 1 cited

Tag-Enriched Multi-Attention with Large Language Models for Cross-Domain Sequential Recommendation

Wangyu Wu, Xuhang Chen, Zhenhong Chen +5

Cross-Domain Sequential Recommendation (CDSR) plays a crucial role in modern consumer electronics and e-commerce platforms, where users interact with diverse services such as books…

cs.CV2025★ 1 cited

Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation

Wangyu Wu, Zhenhong Chen, Xiaowen Ma +6

Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained attention for its cost-effectiveness. Most existing methods emphasize inter-class separation, ofte…

cs.IR2025★ 1 cited

LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendation

Wangyu Wu, Zhenhong Chen, Wenqiao Zhang +5

Cross-Domain Sequential Recommendation (CDSR) predicts user behavior by leveraging historical interactions across multiple domains, focusing on modeling cross-domain preferences an…

cs.CV2025

Cognitive-Inspired Hierarchical Attention Fusion With Visual and Textual for Cross-Domain Sequential Recommendation

Wangyu Wu, Zhenhong Chen, Siqi Song +4

Cross-Domain Sequential Recommendation (CDSR) predicts user behavior by leveraging historical interactions across multiple domains, focusing on modeling cross-domain preferences th…

cs.CV2024★ 1 cited

Image Augmentation Agent for Weakly Supervised Semantic Segmentation

Wangyu Wu, Xianglin Qiu, Siqi Song +4

Weakly-supervised semantic segmentation (WSSS) has achieved remarkable progress using only image-level labels. However, most existing WSSS methods focus on designing new network st…

cs.CV2024★ 44 cited

Adaptive Patch Contrast for Weakly Supervised Semantic Segmentation

Wangyu Wu, Tianhong Dai, Zhenhong Chen +4

Weakly Supervised Semantic Segmentation (WSSS) using only image-level labels has gained significant attention due to its cost-effectiveness. The typical framework involves using im…