Chenlong Yin

Orcid: 0009-0009-3283-0037

According to our database1, Chenlong Yin authored at least 14 papers between 2024 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
PIArena: A Platform for Prompt Injection Evaluation.
CoRR, April, 2026

PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses.
CoRR, March, 2026

2025
PISanitizer: Preventing Prompt Injection to Long-Context LLMs via Prompt Sanitization.
CoRR, November, 2025

The Reasoning Trap: How Enhancing LLM Reasoning Amplifies Tool Hallucination.
CoRR, October, 2025

HRL-Based Proactive Caching Scheme for Vehicle-Edge-Cloud Collaborative System Applications.
IEEE Internet Things J., April, 2025

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.
CoRR, April, 2025

Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

JailbreakDiffBench: A Comprehensive Benchmark for Jailbreaking Diffusion Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

NetSafe: Exploring the Topological Safety of Multi-agent System.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Advance-FL: A3C-Based Adaptive Asynchronous Online Federated Learning for Vehicular Edge Cloud Computing Networks.
IEEE Trans. Intell. Veh., November, 2024

NetSafe: Exploring the Topological Safety of Multi-agent Networks.
CoRR, 2024

Unleash The Power of Pre-Trained Language Models for Irregularly Sampled Time Series.
CoRR, 2024

An MCTS-based Intersection Collaboration Method for Multi-AGV in Automated Container Terminals.
Proceedings of the 22nd IEEE International Conference on Industrial Informatics, 2024

Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach.
Proceedings of the Forty-first International Conference on Machine Learning, 2024


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