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Junlan Feng

10 papers hereh-index 12 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3
  • last author6

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.AI4
same name
  • Junlan Feng — 27 papers, h 17
  • Junlan Feng — 17 papers, h 15
  • Junlan Feng — 16 papers, h 7
  • Junlan Feng — 13 papers, h 3
  • Junlan Feng — 12 papers, h 3
  • Junlan Feng — 8 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

EdgeMem: LLM-Free Agent Memory Construction and Retrieval via Evidence-Preserving Multi-Anchor Hypergraph

Zeyang Cui, Jiannong Cao, Zhiyuan Wen +3

Agent memory allows LLM agents to use earlier interactions when answering new queries. Existing methods often compress interaction histories into summaries or other LLM-generated r…

cs.AI2026

Automated Trajectory Evaluation for Mobile Agents via Step-Level Consequence Reasoning and Aggregation

Pengshuai Yang, Zijing Gao, Xue Yu +3

Evaluating language-guided mobile agents has recently shifted from rule-based to model-based approaches to achieve scalable and automated assessments. However, existing holistic ev…

cs.AI2026

SeerGuard: A Safety Framework for Mobile GUI Agents via World Model Prediction

Xue Yu, Bo Yuan, Kailin Zhao +3

Mobile graphical user interface (GUI) agents have demonstrated remarkable capabilities in automating complex tasks, yet they introduce critical safety risks because a single errone…

cs.AI2026

JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data

Junlan Feng, Fanyu Meng, Chong Long +12

We introduce JT-Safe-V2, a large language model designed to advance the safety and trustworthiness of foundation models, extending our previous JT-Safe model toward a more comprehe…

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