5 citations · 6 across the 13 of their papers we have counts for
5 papers · 1 filter
CURIO: Curiosity-Driven Test-Time Learning for Open-Ended Discovery
Tao Feng, Fangxu Yu, Zijie Lei +5
Open-ended discovery requires learning from repeated attempts while continuing to explore directions whose value is not yet apparent. Search with a frozen large language model (LLM…
Weak-to-Strong On-Policy Distillation
Fangxu Yu, Weijia Xu, Michael Xu +2
On-policy distillation (OPD), which aligns a student with the teacher's token-level distribution on the student's own rollouts, is an effective paradigm for transferring capabiliti…
TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning
Fangxu Yu, Tao Feng, Dehai Min +3
Time series reasoning is essential for real-world problem-solving. While both Large Language Models (LLMs) and Vision-Language Models (VLMs) can reason about time-series data, thei…
FlowBank: Query-Adaptive Agentic Workflows Optimization through Precompute-and-Reuse
Lingzhi Yuan, Chenghao Deng, Fangxu Yu +3
Large Language Model (LLM)-based multi-agent systems are increasingly powerful, but current agentic workflow optimization paradigms make an unsatisfying trade-off. Task-level metho…
COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability
Xingang Guo, Fangxu Yu, Huan Zhang +2
Jailbreaks on large language models (LLMs) have recently received increasing attention. For a comprehensive assessment of LLM safety, it is essential to consider jailbreaks with di…