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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

VisionReasoner: Unified Reasoning-Integrated Visual Perception via Reinforcement Learning

Yuqi Liu, Tianyuan Qu, Zhisheng Zhong +4

Large vision-language models exhibit inherent capabilities to handle diverse visual perception tasks. In this paper, we introduce VisionReasoner, a unified framework capable of rea…

cs.CV2025

RTime-QA: A Benchmark for Atomic Temporal Event Understanding in Large Multi-modal Models

Yuqi Liu, Qin Jin, Tianyuan Qu +4

Understanding accurate atomic temporal event is essential for video comprehension. However, current video-language benchmarks often fall short to evaluate Large Multi-modal Models'…