The AdsMT is designed to capture the intricate relationships between adsorbates and the multiple adsorption sites on surfaces through the cross-attention mechanism, thereby avoiding the enumeration of adsorption configurations. To the best of our knowledge, this is the first work that directly predicts the GMAE of diverse adsorption systems without the acquisition of any site-binding information. As illustrated in Fig. , three GMAE datasets comprising diverse catalyst surfaces and adsorbates were constructed for the challenging GMAE prediction task.