works on

From the 1 of 19 linked papers with an AI index.

collaborators

19 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.CV2026

RePlan: Reasoning-guided Region Planning for Complex Instruction-based Image Editing

Tianyuan Qu, Lei Ke, Xiaohang Zhan +6

The paper presents RePlan, a framework that first reasons about natural‑language instructions to identify specific image regions and then edits those regions using a diffusion mode…

cs.CV2026

Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

Yuqi Liu, Bohao Peng, Zhisheng Zhong +4

Traditional methods for reasoning segmentation rely on supervised fine-tuning with categorical labels and simple descriptions, limiting its out-of-domain generalization and lacking…

cs.CV2026

ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models

Yuqi Liu, Liangyu Chen, Jiazhen Liu +4

Post-training Large Vision-and-Language Models (LVLMs) typically involves Supervised Fine-Tuning (SFT) for knowledge injection or Reinforcement Learning with Verifiable Rewards (RL…

cs.CV2026

VisionZip: Longer is Better but Not Necessary in Vision Language Models

Senqiao Yang, Yukang Chen, Zhuotao Tian +4

Recent advancements in vision-language models have enhanced performance by increasing the length of visual tokens, making them much longer than text tokens and significantly raisin…

cs.CL2026

Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning

Xichen Zhang, Sitong Wu, Yinghao Zhu +4

Reinforcement learning from verifiable rewards has emerged as a powerful technique for enhancing the complex reasoning abilities of Large Language Models (LLMs). However, these met…