{"ID":5438787,"CreatedAt":"2026-07-01T01:17:58.482524686Z","UpdatedAt":"2026-07-03T10:18:46.416236719Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.31451","arxiv_id":"2606.31451","title":"UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation","abstract":"Unified multimodal models (UMMs) have shown great promise in integrating understanding and generation across diverse modalities. However, existing research rarely extends this paradigm to the tactile domain, where both object-level semantics and sensor-level configurations jointly determine the meaning of touch. To address this gap, we propose UniTac, the first UMM designed for tactile understanding and generation. UniTac models the tactile process as a transition from non-contact to contact, capturing the physical interaction between sensors and objects through a dual-level representation that encodes both sensor and object attributes. For tactile understanding, UniTac introduces two tasks, object property description and sensor identification, to enhance reasoning over physical and cross-sensor information. For tactile generation, we design a two-stage training paradigm consisting of reconstruction and alignment, together with a sensor-prior-based sampling strategy that simulates realistic tactile contact. Trained on large-scale multi-sensor datasets, UniTac achieves state-of-the-art performance in tactile understanding and generates realistic tactile signals across sensors.","short_abstract":"Unified multimodal models (UMMs) have shown great promise in integrating understanding and generation across diverse modalities. However, existing research rarely extends this paradigm to the tactile domain, where both object-level semantics and sensor-level configurations jointly determine the meaning of touch. To add...","url_abs":"https://arxiv.org/abs/2606.31451","url_pdf":"https://arxiv.org/pdf/2606.31451v1","authors":"[\"Jiahang Tu\",\"Fengyu Yang\",\"Chenyang Ma\",\"Xihang Yu\",\"Ziyao Zeng\",\"Shaokai Wu\",\"Hanbin Zhao\",\"Zhi Tao\",\"Chao Zhang\",\"Hui Qian\",\"Alex Wong\"]","published":"2026-06-30T10:25:46Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.AI\"]","methods":"[]","has_code":false}