7 papers · 1 filter
TSRL: Trigger-based Supervised Reinforcement Learning for Continual Agent Training
Yuqian Fu, Kaiwen Jiang, Zijun Song +3
Large language model (LLM) agents excel at complex, multi-step tasks but suffer from catastrophic forgetting during continual learning--acquiring new skills often degrades previous…
3SPO: State-Score-Supervised Policy Optimization for LLM Agents
Yu Han, Kailing Li, Yang Jiao +4
Training large language models (LLMs) as autonomous agents via reinforcement learning (RL) has enabled frontier models to achieve superhuman performance in long-horizon tasks. Howe…
When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff
Runze Liu, Jiashun Liu, Xu Wan +2
Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) has become a standard pipeline for Large Language Model (LLM) post-training. SFT is expected to provide a usefu…
A Shared Valence Axis Across Modern LLMs and Human EEG: The Saturation Regularity
Yousef A. Radwan, Xuhui Liu, Kilichbek Haydarov +2
Large language models (LLMs) have emerged as powerful representation learners whose internal features increasingly align with human cognition. We study whether modern LLMs can serv…
Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes
Yuqian Fu, Haohuan Huang, Kaiwen Jiang +4
On-policy distillation (OPD) is increasingly used in LLM post-training because it can leverage a teacher model to provide dense supervision on student rollouts. The standard implem…
MOSAIC: A Universal Agent-Level Interface for Cross-Paradigm Agent Mixing and Human-AI Collaboration
Abdulhamid M. Mousa, Jinhui Pang, Rakhmonberdi Khajiev +5
Existing infrastructure cannot deploy agents from different decision-making paradigms within the same environment, making fair cross-paradigm comparison under identical conditions…
RLAE: Reinforcement Learning-Assisted Ensemble for LLMs
Yuqian Fu, Yuanheng Zhu, Jiajun Chai +4
Ensembling large language models (LLMs) can effectively combine diverse strengths of different models, offering a promising approach to enhance performance across various tasks. Ho…