collaborators

6 papers

cs.AI2026

Visual sensitivity is not claim retractability: persistence-aware credit assignment for multimodal reinforcement learning

Zhongan Bi, Kepeng Lin, Xuanang Gao +2

Reinforcement Learning with Verifiable Rewards (RLVR) has been extended to Large Vision-Language Models (LVLMs), and perception-aware methods further encourage policies to rely on…

cs.LG2026

Quality Determines Direction, Length Shapes Magnitude: Length Control for Open-Ended Reinforcement Learning

Zijun Weng, Zhongan Bi, Xuanang Gao +5

Reinforcement learning (RL) changes not only what language models say, but also how much they say, often increasing response length at the cost of token efficiency. Controlling thi…

cs.CV2026

V-ABS: Action-Observer Driven Beam Search for Dynamic Visual Reasoning

Zhiwei Ning, Xuanang Gao, Jiaxi Cao +6

Multimodal large language models (MLLMs) have achieved remarkable success in general perception, yet complex multi-step visual reasoning remains a persistent challenge. Although re…

cs.CV2026

Fore-Mamba3D: Mamba-based Foreground-Enhanced Encoding for 3D Object Detection

Zhiwei Ning, Xuanang Gao, Jiaxi Cao +5

Linear modeling methods like Mamba have been merged as the effective backbone for the 3D object detection task. However, previous Mamba-based methods utilize the bidirectional enco…

cs.CV2025

CMF-IoU: Multi-Stage Cross-Modal Fusion 3D Object Detection with IoU Joint Prediction

Zhiwei Ning, Zhaojiang Liu, Xuanang Gao +4

Multi-modal methods based on camera and LiDAR sensors have garnered significant attention in the field of 3D detection. However, many prevalent works focus on single or partial sta…

cs.CV2025

FIX-CLIP: Dual-Branch Hierarchical Contrastive Learning via Synthetic Captions for Better Understanding of Long Text

Bingchao Wang, Zhiwei Ning, Jianyu Ding +5

CLIP has shown promising performance across many short-text tasks in a zero-shot manner. However, limited by the input length of the text encoder, CLIP struggles on under-stream ta…