6 papers · 1 filter
ReTerm: Recovery Training for Self-Improving Terminal Agents
Wei Xie, Kaituo Feng, Shiming Fu +3
Terminal agents have shown strong abilities in complex coding tasks. However, they often struggle to recover from errors during long-running execution (e.g., command errors, faulty…
SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation
Zhengbo Jiao, Yiming Cheng, Yilei Jiang +15
Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines construct training data, search…
DOPD: Dual On-policy Distillation
Xinlei Yu, Gen Li, Qingyi Si +13
On-policy distillation (OPD) offers superior capacity transfer by supervising student-sampled trajectories with dense token-level signals. To furnish high-quality supervision sourc…
The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook
Xinlei Yu, Zhangquan Chen, Yongbo He +36
Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an inc…
Exploring Reasoning Reward Model for Agents
Kaixuan Fan, Kaituo Feng, Manyuan Zhang +7
Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However, most methods still relies on sparse…
MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs
Jiakang Yuan, Tianshuo Peng, Yilei Jiang +8
Logical reasoning is a fundamental aspect of human intelligence and an essential capability for multimodal large language models (MLLMs). Despite the significant advancement in mul…