most citedSeed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning

1 citations · 1 across the 12 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

cs.CV2026

VLA-: Learning Physical State Transition for Vision-Language-Action Models

Qi Lu, Jiarun Li, Ce Zhang +5

Vision-language-action (VLA) models transfer semantic knowledge acquired through vision-language pretraining to robot control, achieving strong performance across various benchmark…

cs.CV2026

Ground What You See: Hallucination-Resistant MLLMs via Caption Feedback, Diversity-Aware Sampling, and Conflict Regularization

Miao Pan, Wangjie Gan, Jintao Chen +4

While Multimodal Large Language Models (MLLMs) have achieved remarkable success across diverse tasks, their practical deployment is severely hindered by hallucination issues, which…