[
    {
        "id": "osp-25190",
        "type": "article-journal",
        "title": "Pistis Technical Report",
        "author": [
            {
                "family": "Chen",
                "given": "Heyun"
            },
            {
                "family": "Lan",
                "given": "Xiaohan"
            },
            {
                "family": "Li",
                "given": "Jiaxi"
            },
            {
                "family": "Lu",
                "given": "Zhilin"
            },
            {
                "family": "She",
                "given": "Qi"
            },
            {
                "family": "Xu",
                "given": "Weiwen"
            },
            {
                "family": "Yu",
                "given": "Fei"
            },
            {
                "family": "Zhong",
                "given": "Yu-Jie"
            },
            {
                "family": "Chen",
                "given": "Jinghuan"
            },
            {
                "family": "Feng",
                "given": "Zijian"
            },
            {
                "family": "Jiao",
                "given": "Siyu"
            },
            {
                "family": "Lin",
                "given": "Yiheng"
            },
            {
                "family": "Wang",
                "given": "Xinhao"
            },
            {
                "family": "Yang",
                "given": "Sihan"
            },
            {
                "family": "You",
                "given": "Jieyu"
            },
            {
                "family": "Zhang",
                "given": "Changbin"
            },
            {
                "family": "Zhang",
                "given": "Hengyu"
            },
            {
                "family": "Zhang",
                "given": "Xudong"
            },
            {
                "family": "Zhao",
                "given": "Yunqing"
            },
            {
                "family": "Zheng",
                "given": "Shuai"
            }
        ],
        "URL": "https://omanscience.com/en/articles/pistis-technical-report",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "We introduce the Pistis model family, comprising 27B- and 9B-parameter multimodal large language models built on Qwen3.6 and Qwen3.5, respectively, and developed through a general and scalable post-training framework. The framework first establishes a strong foundation through large-scale multimodal supervised fine-tuning (SFT). Building on this SFT foundation, we propose Interleaved Distillation and Reinforcement Learning (IDRL), a novel post-training paradigm that tightly integrates on-policy distillation and reinforcement learning within a single training loop. By alternating between the two objectives, rather than optimizing either in isolation or combining them in a static joint loss, IDRL enables more effective knowledge transfer, greater optimization stability, and more precise credit assignment for long-horizon agentic trajectories, leading to stronger performance while mitigating common capability trade-offs. At both model scales, the framework produces two specialized variants: Pistis-Thinking, designed to strengthen deep multimodal reasoning, and Pistis-Agentic, which additionally incorporates agentic trajectory data to support long-horizon planning, iterative reasoning, and tool use. Pistis-Agentic is particularly strong in multimodal search. Both scales outperform their corresponding base models. Beyond model-parameter optimization, we further introduce Pistis-Auto-Harnessing (PAH), a system-level method that automatically improves the agent's inference harness through iterative optimization. Experiments demonstrate that PAH enhances the model performance without updating the model parameters or increasing the interaction budget."
    }
]