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Home/Authors/Ran Jin

Ran Jin

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×2ML×2NLP×1Crypto×1HCI×1

Frequent co-authors

Tianyi Men1×
Zhuoran Jin1×
Kang Liu1×
Jun Zhao1×
Haoran Jin1×
Xiting Wang1×

Research Timeline

2026
Understanding User Privacy Perceptions of GenAI Smartphones

This study investigates user perceptions of privacy risks associated with GenAI smartphones, finding that users express heightened concerns across the entire data lifecycle and suggest comprehensive, system-level privacy enhancements.

C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders

The paper introduces C$^2$R (Cross-sample Consistency Regularization) to address feature splitting and absorption issues in Sparse Autoencoders by encouraging consistent latent assignment across samples.

The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation

This paper introduces a controlled environment to study multi-turn long-horizon planning ability acquisition, shaping, and integration in foundation model agents.

Highlighted terms show continued research focus across papers

Papers

cs.CLcs.AIcs.LGEmpiricalRecentJul 27, 2026

The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation

Tianyi Men, Zhuoran Jin, Kang Liu, Jun Zhao

This paper introduces a controlled environment to study multi-turn long-horizon planning ability acquisition, shaping, and integration in foundation model agents.

View →
cs.LGcs.AIEmpirical
Recent
Jun 29, 2026

C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders

Haoran Jin, Xiting Wang, Shijie Ren, Hong Xie +1 more

The paper introduces C$^2$R (Cross-sample Consistency Regularization) to address feature splitting and absorption issues in Sparse Autoencoders by encouraging consistent latent assignment across sampl…

View →
cs.CRcs.HCRecentApr 7, 2026

Understanding User Privacy Perceptions of GenAI Smartphones

Ran Jin, Liu Wang, Shidong Pan, Luona Xu +2 more

This study investigates user perceptions of privacy risks associated with GenAI smartphones, finding that users express heightened concerns across the entire data lifecycle and suggest comprehensive,…

View →