127 citations · 168 across the 38 of their papers we have counts for
8 papers · 1 filter
Data Quality Enhancement on the Basis of Diversity with Large Language Models for Text Classification: Uncovered, Difficult, and Noisy
Min Zeng, Caiquan Liu, Shiqi Zhang +3
In recent years, the use of large language models (LLMs) for text classification has attracted widespread attention. Despite this, the classification accuracy of LLMs has not yet u…
BlueLM-V-3B: Algorithm and System Co-Design for Multimodal Large Language Models on Mobile Devices
Xudong Lu, Yinghao Chen, Cheng Chen +19
The emergence and growing popularity of multimodal large language models (MLLMs) have significant potential to enhance various aspects of daily life, from improving communication t…
A Learning Rate Path Switching Training Paradigm for Version Updates of Large Language Models
Zhihao Wang, Shiyu Liu, Jianheng Huang +5
Due to the continuous emergence of new data, version updates have become an indispensable requirement for Large Language Models (LLMs). The training paradigms for version updates o…
ControlAR: Controllable Image Generation with Autoregressive Models
Zongming Li, Tianheng Cheng, Shoufa Chen +6
Autoregressive (AR) models have reformulated image generation as next-token prediction, demonstrating remarkable potential and emerging as strong competitors to diffusion models. H…
Efficient Test-Time Prompt Tuning for Vision-Language Models
Yuhan Zhu, Guozhen Zhang, Chen Xu +4
Vision-language models have showcased impressive zero-shot classification capabilities when equipped with suitable text prompts. Previous studies have shown the effectiveness of te…
FAGhead: Fully Animate Gaussian Head from Monocular Videos
Yixin Xuan, Xinyang Li, Gongxin Yao +4
High-fidelity reconstruction of 3D human avatars has a wild application in visual reality. In this paper, we introduce FAGhead, a method that enables fully controllable human portr…
EVF-SAM: Early Vision-Language Fusion for Text-Prompted Segment Anything Model
Yuxuan Zhang, Tianheng Cheng, Lianghui Zhu +7
Segment Anything Model (SAM) has attracted widespread attention for its superior interactive segmentation capabilities with visual prompts while lacking further exploration of text…
Meta-Auxiliary Learning for Micro-Expression Recognition
Jingyao Wang, Yunhan Tian, Yuxuan Yang +3
Micro-expressions (MEs) are involuntary movements revealing people's hidden feelings, which has attracted numerous interests for its objectivity in emotion detection. However, desp…