activity
20232026
most citedMisusing Tools in Large Language Models With Visual Adversarial Examples

6 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

An Exploratory Study to Repurpose LLMs to a Unified Architecture for Time Series Classification

Hansen He, Shuheng Li

Time series classification (TSC) is a core machine learning problem with broad applications. Recently there has been growing interest in repurposing large language models (LLMs) fo…

cs.CV2025

Matching Skeleton-based Activity Representations with Heterogeneous Signals for HAR

Shuheng Li, Jiayun Zhang, Xiaohan Fu +3

In human activity recognition (HAR), activity labels have typically been encoded in one-hot format, which has a recent shift towards using textual representations to provide contex…

cs.LG2025

Orthogonal Calibration for Asynchronous Federated Learning

Jiayun Zhang, Shuheng Li, Haiyu Huang +3

Asynchronous federated learning mitigates the inefficiency of conventional synchronous aggregation by integrating updates as they arrive and adjusting their influence based on stal…

cs.CY2024★ 1 cited

Creating a Cooperative AI Policymaking Platform through Open Source Collaboration

Aiden Lewington, Alekhya Vittalam, Anshumaan Singh +48

Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Curre…

cs.CR2024★ 2 cited

Imprompter: Tricking LLM Agents into Improper Tool Use

Xiaohan Fu, Shuheng Li, Zihan Wang +4

Large Language Model (LLM) Agents are an emerging computing paradigm that blends generative machine learning with tools such as code interpreters, web browsing, email, and more gen…

eess.SP2024★ 1 cited

UniMTS: Unified Pre-training for Motion Time Series

Xiyuan Zhang, Diyan Teng, Ranak Roy Chowdhury +4

Motion time series collected from mobile and wearable devices such as smartphones and smartwatches offer significant insights into human behavioral patterns, with wide applications…

cs.CR2023★ 6 cited

Misusing Tools in Large Language Models With Visual Adversarial Examples

Xiaohan Fu, Zihan Wang, Shuheng Li +4

Large Language Models (LLMs) are being enhanced with the ability to use tools and to process multiple modalities. These new capabilities bring new benefits and also new security ri…