5 papers
Agent-Omni: Test-Time Multimodal Reasoning via Model Coordination for Understanding Anything
Huawei Lin, Yunzhi Shi, Tong Geng +3
Multimodal large language models (MLLMs) have shown strong capabilities but remain limited to fixed modality pairs and require costly fine-tuning with large aligned datasets. Build…
VTBench: Evaluating Visual Tokenizers for Autoregressive Image Generation
Huawei Lin, Tong Geng, Zhaozhuo Xu +1
Autoregressive (AR) models have recently shown strong performance in image generation, where a critical component is the visual tokenizer (VT) that maps continuous pixel inputs to…
ALinFiK: Learning to Approximate Linearized Future Influence Kernel for Scalable Third-Party LLM Data Valuation
Yanzhou Pan, Huawei Lin, Yide Ran +5
Large Language Models (LLMs) heavily rely on high-quality training data, making data valuation crucial for optimizing model performance, especially when working within a limited bu…
UniGuardian: A Unified Defense for Detecting Prompt Injection, Backdoor Attacks and Adversarial Attacks in Large Language Models
Huawei Lin, Yingjie Lao, Tong Geng +2
Large Language Models (LLMs) are vulnerable to attacks like prompt injection, backdoor attacks, and adversarial attacks, which manipulate prompts or models to generate harmful outp…
Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data
Huawei Lin, Jun Woo Chung, Yingjie Lao +1
Gradient Boosting Decision Tree (GBDT) is one of the most popular machine learning models in various applications. However, in the traditional settings, all data should be simultan…