[
    {
        "id": "osp-26675",
        "type": "article-journal",
        "title": "Map2Route: Benchmarking Compositional Language-Grounded Route Planning over Semantic Maps",
        "author": [
            {
                "family": "Bao",
                "given": "Muyi"
            },
            {
                "family": "Xu",
                "given": "Hang"
            },
            {
                "family": "Tang",
                "given": "Jingfan"
            },
            {
                "family": "Liu",
                "given": "Zihan"
            },
            {
                "family": "Cai",
                "given": "Yuxin"
            },
            {
                "family": "Lv",
                "given": "Chen"
            },
            {
                "family": "Wang",
                "given": "Wenshan"
            },
            {
                "family": "Zhang",
                "given": "Ji"
            }
        ],
        "URL": "https://omanscience.com/en/articles/map2route-benchmarking-compositional-language-grounded-route-planning-over-semantic-maps",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "We introduce Map2Route, a human-curated benchmark for compositional language-grounded route planning over pre-built semantic maps. Map2Route contains 1,000 episodes across 40 scenes, where instructions use relational, comparative, and nested descriptions to identify route-relevant objects and regions, while specifying ordered must-pass regions, must-avoid requirements, five categories of soft preferences, and spatial and route-stage scopes, which is partially tested by existing works. Alongside Map2Route, we propose Grounding2Route, which combines executable code-as-grounding with verification-guided repair and scope-aware planning.Across seven representative adapted baselines, Grounding2Route substantially outperforms existing methods in all metrics. Despite these gains, a substantial gap to human demonstrations remains, highlighting the difficulty of Map2Route and the considerable headroom for future progress. Additional qualitative results and resources are available on https://anonymous.4open.science/w/Map2Route-F05F/."
    }
]