5 papers
CrowdVLM-R1: Expanding R1 Ability to Vision Language Model for Crowd Counting using Fuzzy Group Relative Policy Reward
Zhiqiang Wang, Pengbin Feng, Yanbin Lin +4
We propose Fuzzy Group Relative Policy Reward (FGRPR), a novel framework that integrates Group Relative Policy Optimization (GRPO) with a fuzzy reward function to enhance learning…
Adaptable and Reliable Text Classification using Large Language Models
Zhiqiang Wang, Yiran Pang, Yanbin Lin +1
Text classification is fundamental in Natural Language Processing (NLP), and the advent of Large Language Models (LLMs) has revolutionized the field. This paper introduces an adapt…
Problematic Tokens: Tokenizer Bias in Large Language Models
Jin Yang, Zhiqiang Wang, Yanbin Lin +1
Recent advancements in large language models(LLMs), such as GPT-4 and GPT-4o, have shown exceptional performance, especially in languages with abundant resources like English, than…
Benchmarking Large Language Models for Image Classification of Marine Mammals
Yijiashun Qi, Shuzhang Cai, Zunduo Zhao +3
As Artificial Intelligence (AI) has developed rapidly over the past few decades, the new generation of AI, Large Language Models (LLMs) trained on massive datasets, has achieved gr…
LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
Zhiqiang Wang, Dejia Xu, Rana Muhammad Shahroz Khan +3
Image geolocation is a critical task in various image-understanding applications. However, existing methods often fail when analyzing challenging, in-the-wild images. Inspired by t…