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Home/Authors/Ping Chen

Ping Chen

4 indexed papers

Recent (6 mo)
4
With code
0
Influential cites
0
Benchmarked
0

Publications per year

4
26

Top categories

AI×3Crypto×2NLP×1Vision×1ML×1Info Retrieval×1Emerging Tech×1Software Eng.×1

Frequent co-authors

Dongping Chen1×
Xuanao Huang1×
Zhihan Hu1×
Qingyuan Shi1×
Dianqi Li1×
Tianyi Zhou1×

Research Timeline

2026
Clawed and Dangerous: Can We Trust Open Agentic Systems?

This paper systematizes the security challenges of open agentic systems, concluding that while attack characterization is mature, the field lacks robust guidelines for operational governance, memory integrity, and capability revocation.

When Alignment Isn't Enough: Response-Path Attacks on LLM Agents

This paper introduces the Relay Tampering Attack (RTA), demonstrating that malicious third-party relays can undermine the security of LLM agents by modifying responses post-alignment, even if the LLM itself is perfectly aligned.

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation

LoopFM proposes a novel framework to significantly improve knowledge distillation for recommendation systems by structuring the rich intermediate embeddings of large foundation models as input features, thereby overcoming the limitations of single-scalar prediction transfer.

Sandboxed Coding Agents are Competitive Omni-modal Task Solvers

The paper demonstrates that specialized coding agents, using only text and image access within a sandbox, can effectively solve complex omnimodal tasks, often outperforming state-of-the-art native omnimodal models.

Highlighted terms show continued research focus across papers

Papers

cs.CLcs.CVRecentMay 30, 2026

Sandboxed Coding Agents are Competitive Omni-modal Task Solvers

Dongping Chen, Xuanao Huang, Zhihan Hu, Qingyuan Shi +2 more

The paper demonstrates that specialized coding agents, using only text and image access within a sandbox, can effectively solve complex omnimodal tasks, often outperforming state-of-the-art native omn…

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cs.LGcs.AIcs.IRRecentMay 28, 2026

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation

Shali Jiang, Hua Zheng, Boyang Liu, Laming Chen +39 more

LoopFM proposes a novel framework to significantly improve knowledge distillation for recommendation systems by structuring the rich intermediate embeddings of large foundation models as input feature…

View →
cs.CRcs.AIRecentMay 4, 2026

When Alignment Isn't Enough: Response-Path Attacks on LLM Agents

Mingyu Luo, Zihan Zhang, Zesen Liu, Yuchong Xie +6 more

This paper introduces the Relay Tampering Attack (RTA), demonstrating that malicious third-party relays can undermine the security of LLM agents by modifying responses post-alignment, even if the LLM…

View →
cs.CRcs.AIcs.ETRecentMar 27, 2026

Clawed and Dangerous: Can We Trust Open Agentic Systems?

Shiping Chen, Qin Wang, Guangsheng Yu, Xu Wang +1 more

This paper systematizes the security challenges of open agentic systems, concluding that while attack characterization is mature, the field lacks robust guidelines for operational governance, memory i…

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