6 citations · 12 across the 10 of their papers we have counts for
10 papers
ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning
Yeyuan Wang, Dehong Gao, Rujiao Long +4
Direct Preference Optimization (DPO) has gained significant attention for its simplicity and computational efficiency in aligning large language models (LLMs). Recent advancements…
Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
Bin Li, Dehong Gao, Yeyuan Wang +4
Despite the significant success of Large Vision-Language models(LVLMs), these models still suffer hallucinations when describing images, generating answers that include non-existen…
CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models
Yeyuan Wang, Dehong Gao, Bin Li +7
The impressive performance of Large Language Model (LLM) has prompted researchers to develop Multi-modal LLM (MLLM), which has shown great potential for various multi-modal tasks.…
MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning
Yufei Ma, Zihan Liang, Huangyu Dai +9
The growing demand for larger-scale models in the development of \textbf{L}arge \textbf{L}anguage \textbf{M}odels (LLMs) poses challenges for efficient training within limited comp…
MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction
Zhiming Yang, Haining Gao, Dehong Gao +5
Click-through rate (CTR) prediction is one of the fundamental tasks in the industry, especially in e-commerce, social media, and streaming media. It directly impacts website revenu…
General2Specialized LLMs Translation for E-commerce
Kaidi Chen, Ben Chen, Dehong Gao +6
Existing Neural Machine Translation (NMT) models mainly handle translation in the general domain, while overlooking domains with special writing formulas, such as e-commerce and le…
Cross-channel Budget Coordination for Online Advertising System
Guangyuan Shen, Shenjie Sun, Dehong Gao +4
In online advertising (Ad), advertisers are always eager to know how to globally optimize their budget allocation strategies across different channels for more conversions such as…
EdgeNet : Encoder-decoder generative Network for Auction Design in E-commerce Online Advertising
Guangyuan Shen, Shengjie Sun, Dehong Gao +3
We present a new encoder-decoder generative network dubbed EdgeNet, which introduces a novel encoder-decoder framework for data-driven auction design in online e-commerce advertisi…
Fast Heterogeneous Federated Learning with Hybrid Client Selection
Guangyuan Shen, Dehong Gao, Duanxiao Song +5
Client selection schemes are widely adopted to handle the communication-efficient problems in recent studies of Federated Learning (FL). However, the large variance of the model up…
Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection
Guangyuan Shen, Dehong Gao, Libin Yang +4
Client selection strategies are widely adopted to handle the communication-efficient problem in recent studies of Federated Learning (FL). However, due to the large variance of the…