activity
20232026
most citedMobileSteward: Integrating Multiple App-Oriented Agents with Self-Evolution to Automate Cross-App Instructions

6 citations · 9 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CR2026

Hackers or Hallucinators? A Comprehensive Analysis of LLM-Based Automated Penetration Testing

Jiaren Peng, Zeqin Li, Chang You +17

The rapid advancement of Large Language Models (LLMs) has created new opportunities for Automated Penetration Testing (AutoPT), spawning numerous frameworks aimed at achieving end-…

cs.CR2025

From Retrieval to Reasoning: A Framework for Cyber Threat Intelligence NER with Explicit and Adaptive Instructions

Jiaren Peng, Hongda Sun, Xuan Tian +3

The automation of Cyber Threat Intelligence (CTI) relies heavily on Named Entity Recognition (NER) to extract critical entities from unstructured text. Currently, Large Language Mo…

cs.CL2025

Enhancing Medical Dialogue Generation through Knowledge Refinement and Dynamic Prompt Adjustment

Hongda Sun, Jiaren Peng, Wenzhong Yang +3

Medical dialogue systems (MDS) have emerged as crucial online platforms for enabling multi-turn, context-aware conversations with patients. However, existing MDS often struggle to…

cs.MA2025★ 6 cited

MobileSteward: Integrating Multiple App-Oriented Agents with Self-Evolution to Automate Cross-App Instructions

Yuxuan Liu, Hongda Sun, Wei Liu +3

Mobile phone agents can assist people in automating daily tasks on their phones, which have emerged as a pivotal research spotlight. However, existing procedure-oriented agents str…

cs.CL2025

BiDeV: Bilateral Defusing Verification for Complex Claim Fact-Checking

Yuxuan Liu, Hongda Sun, Wenya Guo +4

Complex claim fact-checking performs a crucial role in disinformation detection. However, existing fact-checking methods struggle with claim vagueness, specifically in effectively…

cs.AI2024★ 1 cited

Mobile-Bench: An Evaluation Benchmark for LLM-based Mobile Agents

Shihan Deng, Weikai Xu, Hongda Sun +8

With the remarkable advancements of large language models (LLMs), LLM-based agents have become a research hotspot in human-computer interaction. However, there is a scarcity of ben…

cs.CL2024★ 1 cited

MockLLM: A Multi-Agent Behavior Collaboration Framework for Online Job Seeking and Recruiting

Hongda Sun, Hongzhan Lin, Haiyu Yan +3

Online recruitment platforms have reshaped job-seeking and recruiting processes, driving increased demand for applications that enhance person-job matching. Traditional methods gen…

cs.CL2024

Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering

Hongda Sun, Yuxuan Liu, Chengwei Wu +5

Open-domain question answering (ODQA) has emerged as a pivotal research spotlight in information systems. Existing methods follow two main paradigms to collect evidence: (1) The \t…

cs.AI2023★ 1 cited

Collaborative Synthesis of Patient Records through Multi-Visit Health State Inference

Hongda Sun, Hongzhan Lin, Rui Yan

Electronic health records (EHRs) have become the foundation of machine learning applications in healthcare, while the utility of real patient records is often limited by privacy an…

cs.AI2023

DetermLR: Augmenting LLM-based Logical Reasoning from Indeterminacy to Determinacy

Hongda Sun, Weikai Xu, Wei Liu +5

Recent advances in large language models (LLMs) have revolutionized the landscape of reasoning tasks. To enhance the capabilities of LLMs to emulate human reasoning, prior studies…