---
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id: "53b6f61930163b4c6c4972bc3087189ccba48c0d39a72ab68639ff7fb411dbdd"
canonical_url: "https://aidr.today/53b6f619?lang=en"
title: "Learning Heterogeneous Tactile Representation for General Dexterous Manipulation"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-11-10T00:00:00.000Z"
category: "Research"
topics: ["agent"]
source_urls: ["https://huggingface.co/papers/2611.12806"]
summary: "LingBot-Touch is a tactile foundation model developed to free tactile understanding from sensor-specific physics. The model yields a unified representation across piezoresistive, magnetic, and visuotactile sensors. The resulting tactile tokens can be seamlessly integrated into policy models across paradigms like diffusion policy and vision-language-action (VLA) models."
---

# Learning Heterogeneous Tactile Representation for General Dexterous Manipulation

> [Open the canonical story](<https://aidr.today/53b6f619?lang=en>)

**Published:** 2026-11-10T00:00:00.000Z
**Category:** Research
**Topics:** agent

## Summary

LingBot\-Touch is a tactile foundation model developed to free tactile understanding from sensor\-specific physics\. The model yields a unified representation across piezoresistive, magnetic, and visuotactile sensors\. The resulting tactile tokens can be seamlessly integrated into policy models across paradigms like diffusion policy and vision\-language\-action \(VLA\) models\.

## Sources

- [Story source](<https://huggingface.co/papers/2611.12806>)