2 citations · 7 across the 29 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning
Shujin Wu, Cheng Qian, Xiusi Chen +1
Test-time scaling through iterative self-evolution with environment feedback, as demonstrated by AlphaEvolve, shows remarkable performance gains. We hypothesize that the success of…
cs.LG2025
Self-Improving LLM Agents at Test-Time
Emre Can Acikgoz, Cheng Qian, Heng Ji +2
One paradigm of language model (LM) fine-tuning relies on creating large training datasets, under the assumption that high quantity and diversity will enable models to generalize t…
cs.LG2025
SafeSwitch: Steering Unsafe LLM Behavior via Internal Activation Signals
Peixuan Han, Cheng Qian, Xiusi Chen +3
Large language models (LLMs) exhibit exceptional capabilities across various tasks but also pose risks by generating harmful content. Existing safety mechanisms, while improving mo…