1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.AI2026
ODESteer: A Unified ODE-Based Steering Framework for LLM Alignment
Hongjue Zhao, Haosen Sun, Jiangtao Kong +8
Activation steering, or representation engineering, offers a lightweight approach to align large language models (LLMs) by manipulating their internal activations at inference time…
cs.SE2026
Towards Comprehensive Benchmarking Infrastructure for LLMs In Software Engineering
Daniel Rodriguez-Cardenas, Xiaochang Li, Marcos Macedo +5
Large language models for code are advancing fast, yet our ability to evaluate them lags behind. Current benchmarks focus on narrow tasks and single metrics, which hide critical ga…
cs.LG2025★ 1 cited
P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices
Wei Fan, JinYi Yoon, Xiaochang Li +2
Split Learning (SL) is an emerging privacy-preserving machine learning technique that enables resource constrained edge devices to participate in model training by partitioning a m…