6 papers
SelPE: Progressive Selection for Private Structured Text Synthesis
Xuancheng Zhu, Guoshun Nan, Han Zhang +6
Many data-driven applications rely on structured textual records, such as clinical triage notes and financial transaction logs, for downstream learning and decision-making. In priv…
AutoRAS: Learning Robust Agentic Systems with Primitive Representations
Yang Yue, Xuancheng Zhu, Yuyang Ma +7
The automated design of agentic systems offers a promising pathway for scaling large language models (LLMs) beyond single-agent reasoning. While prior work has advanced task perfor…
LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents
Haoyang Fang, Wei Zhu, Boran Han +11
RL post-training strategies are dataset-dependent and reveal a recurring empirical pattern: capacity parameters accumulate monotonically across stages, while regularization paramet…
See First, Answer Later: Visual Evidence Pre-Alignment via Sufficiency-Driven RL
Yilian Liu, Sicong Leng, Guoshun Nan +7
Multimodal large language models (MLLMs) integrate strong text reasoning with visual inputs, yet their responses can be inconsistent with the underlying images, indicating ineffect…
ReSkill: Reconciling Skill Creation with Policy Optimization in Agentic RL
Zelin He, Haotian Lin, Boran Han +6
Agentic reinforcement learning (RL) enables LLM agents to improve continuously from environment rewards, yet the resulting policies do not systematically accumulate reusable strate…
Can LLM Agents Sustain Long-Horizon Organizational Dynamics?
Xuancheng Zhu, Yang Yue, Shuaibing Wan +4
Large language agents are increasingly used for social simulation, yet it remains unclear whether they can sustain coherent behavior in structured organizations, where goals must p…