most citedLeveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers

3 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

X-Mind: Efficient Visual Chain-of-Thought via Predictive World Model for End-to-End Driving

Bohao Zhao, Chengrui Wei, Guangfeng Jiang +17

Predicting future states is essential for autonomous agents, yet current Vision-Language-Action (VLA) models fundamentally lack this capability, relying instead on reactive percept…

cs.CV2026

X-Foresight: A Joint Vision-Action Causal Forecasting Network via Predictive World Modeling

Baolu Li, Jingyu Qian, Rui Guo +17

Physical world knowledge resides mainly in videos. Equipping Vision-Language-Action (VLA) models with such knowledge is fundamental for safe and generalizable planning. Predictive…

cs.SE2026

Composer 2 Technical Report

Cursor Research, :, Aaron Chan +53

Composer 2 is a specialized model designed for agentic software engineering. The model demonstrates strong long-term planning and coding intelligence while maintaining the ability…

cs.LG2024★ 3 cited

Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers

Jinsong Chen, Hanpeng Liu, John E. Hopcroft +1

While tokenized graph Transformers have demonstrated strong performance in node classification tasks, their reliance on a limited subset of nodes with high similarity scores for co…

cs.CV2024

You Only Need Less Attention at Each Stage in Vision Transformers

Shuoxi Zhang, Hanpeng Liu, Stephen Lin +1

The advent of Vision Transformers (ViTs) marks a substantial paradigm shift in the realm of computer vision. ViTs capture the global information of images through self-attention mo…