works on

From the 1 of 9 linked papers with an AI index.

activity
20242026
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9 papers

cs.CV2026

CoRe: A Comprehensive Framework for Cross-Image Comparative Reasoning in Vision-Language Models

Lin Peng, Cong Wan, Zeyu Guo +2

The paper introduces CoRe, a framework that improves vision-language models' ability to perform fine-grained cross‑image comparative reasoning by providing a large triplet‑based da…

cs.AI2026

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI

Kairos Team, Fei Wang, Shan You +21

We introduce \textbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world model should not aim to fully si…

cs.CV2026

ReMoT: Reinforcement Learning with Motion Contrast Triplets

Cong Wan, Zeyu Guo, Jiangyang Li +5

We present ReMoT, a unified training paradigm to systematically address the fundamental shortcomings of VLMs in spatio-temporal consistency -- a critical failure point in navigatio…

cs.CV2026

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning

Cong Wan, Ying He, Zhongzhan Huang +1

Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources during inference. Recent advan…

cs.CV2026

ProSR: Process-Shaped Spatial Reasoning for Reliable Chain-of-Thought in VLMs

Jiangyang Li, Cong Wan, Changjie Wu +8

Reliable spatial reasoning remains a core bottleneck for vision-language models (VLMs). Existing mainstream training paradigms for spatial reasoning largely rely on outcome alignme…

cs.CV2026

Trajectory-Diversity-Driven Robust Vision-and-Language Navigation

Jiangyang Li, Cong Wan, SongLin Dong +4

Vision-and-Language Navigation (VLN) requires agents to navigate photo-realistic environments following natural language instructions. Current methods predominantly rely on imitati…