5 papers
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…
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…
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…
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…
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…