Publications (10)
What Kind of Visual Tokens Do We Need? Training-free Visual Token Pruning for Multi-modal Large Language Models from the Perspective of Graph
Yutao Jiang, Qiong Wu, Wenhao Lin +2
Recent Multimodal Large Language Models(MLLMs) often use a large number of visual tokens to compensate their visual shortcoming, leading to excessive computation and obvious visual…
Generative Data Augmentation for Non-IID Problem in Decentralized Clinical Machine Learning
Zirui Wang, Shaoming Duan, Chengyue Wu +4
Swarm learning (SL) is an emerging promising decentralized machine learning paradigm and has achieved high performance in clinical applications. SL solves the problem of a central…
Privacy Preservation by Intermittent Transmission in Cooperative LQG Control Systems
Wenhao Lin, Yuqing Ni, Wen Yang +1
In this paper, we study a cooperative linear quadratic Gaussian (LQG) control system with a single user and a server. In this system, the user runs a process and employs the server…
iEnhancer-ELM: improve enhancer identification by extracting position-related multiscale contextual information based on enhancer language models
Jiahao Li, Zhourun Wu, Wenhao Lin +4
Motivation: Enhancers are important cis-regulatory elements that regulate a wide range of biological functions and enhance the transcription of target genes. Although many feature…
Analytical Prediction of Voltage Collapse in Current-Limited Grid-Forming Inverters
Wenhao Lin, Robin Preece, Panagiotis N. Papadopoulos
The limited overcurrent capability of grid-forming (GFM) inverters makes current limiting essential during large disturbances. Activation of a circular current limiter (CCL) does n…
DreamGuard: Efficient Runtime Guardrail for LLM Agents via Risk-Aware World Model
Wenhao Lin, Chenyu Yu, Xingwei Lin +6
As large language model (LLM) agents increasingly invoke external tools and interact with real-world systems, unsafe actions may cause irreversible consequences on external states,…
Accelerating Multimodal Large Language Models via Dynamic Visual-Token Exit and the Empirical Findings
Qiong Wu, Wenhao Lin, Yiyi Zhou +4
The excessive use of visual tokens in existing Multimoal Large Language Models (MLLMs) often exhibits obvious redundancy and brings in prohibitively expensive computation. To gain…
Fit and Prune: Fast and Training-free Visual Token Pruning for Multi-modal Large Language Models
Weihao Ye, Qiong Wu, Wenhao Lin +1
Recent progress in Multimodal Large Language Models(MLLMs) often use large image tokens to compensate the visual shortcoming of MLLMs, which not only exhibits obvious redundancy bu…
ICON: Intent-Context Coupling for Efficient Multi-Turn Jailbreak Attack
Xingwei Lin, Wenhao Lin, Sicong Cao +4
Multi-turn jailbreak attacks have emerged as a critical threat to Large Language Models (LLMs), bypassing safety mechanisms by progressively constructing adversarial contexts from…
An Open-Source Fast Parallel Routing Approach for Commercial FPGAs
Xinshi Zang, Wenhao Lin, Shiju Lin +2
In the face of escalating complexity and size of contemporary FPGAs and circuits, routing emerges as a pivotal and time-intensive phase in FPGA compilation flows. In response to th…