activity
20242026
most citedRT-OVAD: Real-Time Open-Vocabulary Aerial Object Detection via Image-Text Collaboration

2 citations · 2 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2026

SubRot: Signed Gradient Subspace Calibration for VLM Rotation Quantization

Zhenhao Shang, Haizhao Jing, Haokui Zhang +4

Post-training quantization reduces the deployment cost of vision-language models (VLMs), but preserving multimodal capabilities at low bit widths remains challenging. Existing meth…

cs.CV2026

P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration

Haizhao Jing, Zhenhao Shang, Haokui Zhang +2

Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory costs hinder efficient deploy…

cs.CV2026

Rethinking Practical and Efficient Quantization Calibration for Vision-Language Models

Zhenhao Shang, Haizhao Jing, Guoting Wei +4

Post-training quantization (PTQ) is a primary approach for deploying large language models without fine-tuning, and the quantized performance is often strongly affected by the cali…

cs.CV2026

Open-Text Aerial Detection: A Unified Framework For Aerial Visual Grounding And Detection

Guoting Wei, Xia Yuan, Yang Zhou +6

Open-Vocabulary Aerial Detection (OVAD) and Remote Sensing Visual Grounding (RSVG) have emerged as two key paradigms for aerial scene understanding. However, each paradigm suffers…

cs.CV2026

TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models

Haokui Zhang, Congyang Ou, Dawei Yan +5

Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most existing methods rely on heuristic…

cs.CV2025

UVLM: Benchmarking Video Language Model for Underwater World Understanding

Xizhe Xue, Yang Zhou, Dawei Yan +5

Recently, the remarkable success of large language models (LLMs) has achieved a profound impact on the field of artificial intelligence. Numerous advanced works based on LLMs have…

cs.LG2025

Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learning

Haizhao Jing, Haokui Zhang, Zhenhao Shang +3

Neural Architecture Representation Learning aims to transform network models into feature representations for predicting network attributes, playing a crucial role in deploying and…

cs.CV2025

OS-W2S: An Automatic Labeling Engine for Language-Guided Open-Set Aerial Object Detection

Guoting Wei, Yu Liu, Xia Yuan +7

In recent years, language-guided open-set aerial object detection has gained significant attention due to its better alignment with real-world application needs. However, due to li…

cs.CV2024★ 2 cited

RT-OVAD: Real-Time Open-Vocabulary Aerial Object Detection via Image-Text Collaboration

Guoting Wei, Xia Yuan, Yu Liu +7

Aerial object detection plays a crucial role in numerous applications. However, most existing methods focus on detecting predefined object categories, limiting their applicability…