activity
20212026
most citedTowards Semi-supervised Universal Graph Classification

47 citations · 68 across the 14 of their papers we have counts for

collaborators

21 papers

cs.CL2026

Switch Attention: Towards Dynamic and Fine-grained Hybrid Transformers

Yusheng Zhao, Hourun Li, Bohan Wu +5

The attention mechanism has been the core component in modern transformer architectures. However, the computation of standard full attention scales quadratically with the sequence…

cs.CV2026

Detached Skip-Links and -Probe: Decoupling Feature Aggregation from Gradient Propagation for MLLM OCR

Ziye Yuan, Ruchang Yao, Chengxin Zheng +3

Multimodal large language models (MLLMs) excel at high-level reasoning yet fail on OCR tasks where fine-grained visual details are compromised or misaligned. We identify an overloo…

cs.LG2026

DREAM: Dual-Standard Semantic Homogeneity with Dynamic Optimization for Graph Learning with Label Noise

Yusheng Zhao, Jiaye Xie, Qixin Zhang +5

Graph neural networks (GNNs) have been widely used in various graph machine learning scenarios. Existing literature primarily assumes well-annotated training graphs, while the reli…

cs.CL20252 cited

Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs

Yangning Li, Weizhi Zhang, Yuyao Yang +17

Retrieval-Augmented Generation (RAG) lifts the factuality of Large Language Models (LLMs) by injecting external knowledge, yet it falls short on problems that demand multi-step inf…

cs.IR2025

From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents

Weizhi Zhang, Yangning Li, Yuanchen Bei +20

Information retrieval is a cornerstone of modern knowledge acquisition, enabling billions of queries each day across diverse domains. However, traditional keyword-based search engi…

cs.CL2025

MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning

Yusheng Zhao, Xiao Luo, Weizhi Zhang +4

The ability to reason is one of the most fundamental capabilities of large language models (LLMs), enabling a wide range of downstream tasks through sophisticated problem-solving.…