activity
20232026
most citedIgniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents

11 citations · 32 across the 35 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

HLL: Can Agents Cross Humanity's Last Line of Verification?

Xinhao Song, Su Su, Sirui Song +6

Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute for humans in workflows that…

cs.AI2026

Faithful Mobile GUI Agents with Guided Advantage Estimator

Haowen Hu, Pengzhou Cheng, Zheng Wu +3

Vision-language model based graphical user interface (GUI) agents have shown strong interaction capabilities. However, they often behave unfaithfully, relying on memorized shortcut…

cs.AI2026

SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents

Xinshun Feng, Xinhao Song, Lijun Li +2

Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) have demonstrated significant potential in single-turn reasoning tasks. With the paradigm shift toward self…

cs.AI2025

Training High-Level Schedulers with Execution-Feedback Reinforcement Learning for Long-Horizon GUI Automation

Zehao Deng, Tianjie Ju, Zheng Wu +2

The rapid development of large vision-language model (VLM) has greatly promoted the research of GUI agent. However, GUI agents still face significant challenges in handling long-ho…

cs.AI2025

Reasoning or Rambling? Exploring the Effect of Thinking on Agent Persuasion

Haodong Zhao, Jidong Li, Zhaomin Wu +4

Understanding persuasion is critical for the safety and reliability of multi-agent systems built on large language models (LLMs). This paper studies persuasion dynamics by contrast…

cs.AI2025★ 1 cited

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles

Zongru Wu, Rui Mao, Zhiyuan Tian +7

The advent of multimodal agents facilitates effective interaction within graphical user interface (GUI), especially in ubiquitous GUI control. However, their inability to reliably…

cs.AI2024★ 1 cited

MKF-ADS: Multi-Knowledge Fusion Based Self-supervised Anomaly Detection System for Control Area Network

Pengzhou Cheng, Zongru Wu, Gongshen Liu

Control Area Network (CAN) is an essential communication protocol that interacts between Electronic Control Units (ECUs) in the vehicular network. However, CAN is facing stringent…