activity
20242026
collaborators

9 papers

cs.CV2026

MemVLN: Episodic and Procedural Memory for Vision-and-Language Navigation

Yuqi Liu, Shengju Qian, Tianyuan Qu +5

Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to maintain long-horizon visual history for trajectory consistency while executing actions with l…

cs.IR2026

AgenticRec: A Recommendation-Oriented Agentic Framework with Progressive Tool-Integrated Reasoning Optimization

Tianyi Li, Zixuan Wang, Guidong Lei +2

Recommender agents built on Large Language Models offer a promising paradigm for personalized recommendation. However, existing agents typically suffer from a misalignment between…

cs.CV2026

SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation

Shilin Ma, Chubin Zhang, Changyuan Wang +6

Real-time inference of vision-language-action (VLA) models is essential for robotic control. While visual token pruning has shown strong potential for accelerating inference, most…

cs.RO2026

VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models

Zixuan Wang, Yuxin Chen, Yuqi Liu +6

Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to control signals. This "black-box" mapping forces a single forward pass…

cs.RO2026

StarVLA-: Reducing Complexity in Vision-Language-Action Systems

Jinhui Ye, Ning Gao, Senqiao Yang +7

Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landscape remains highly fragmented…

cs.AI2026

Unified-MAS: Universally Generating Domain-Specific Nodes for Empowering Automatic Multi-Agent Systems

Hehai Lin, Yu Yan, Zixuan Wang +6

Automatic Multi-Agent Systems (MAS) generation has emerged as a promising paradigm for solving complex reasoning tasks. However, existing frameworks are fundamentally bottlenecked…