: A Tool-Augmented Multi-Agent Framework for Long Visual Document Understanding
Dawei Zhu, Rui Meng, Jie-Feng Chen et al.
· 0 citations
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MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement
The MiMo-V2.6 series is introduced, an omni-modal family that pushes the frontier of model intelligence by scaling RL compute by building infrastructure for mixed-task agentic RL, including a unified trajectory representation, high-concurrency multi-framework rollout, decoupled control and data planes, and training-inf...
Xiao-Zhen Qiao, Zi-Yue Hua, Zi-Rui Ou et al.
· 10 citations
PaperBanana-Interact: Scientific Diagram Refinement with Multi-Turn Human Feedback
MTPaperBananaBench, a benchmark for multi-turn diagram generation containing 292 images annotated with 3,518 user requirements, is presented and PaperBanana-Interact, a multi-agent system that refines diagrams via an internal critique-and-refine loop is introduced.
Xue-Qing Wu, Ashwin Balasubramanian, Bing-Xuan Li et al.
· 0 citations
PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems
This work introduces PersonaForge, a user simulation framework for synthesizing realistic multi-turn user--agent interactions that combines a four-dimensional persona space, SOUL-driven behavioral control calibrated to real-user statistics, and Reverse Deep Construction grounded in authentic seed queries.
Hanglong Lv, Dawei Zhu, Lei Li et al.
· 0 citations