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MULTISEISMO: A Multimodal Seismic Dataset and Model for Cross-Modal Seismic Understanding

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arXiv:2605. 26320v1 Announce Type: new Abstract: The application of generalist multimodal models (GMMs) to specialized scientific domains remains limited due to the scarcity of comprehensive domain-specific datasets that integrate multiple data modalities beyond text and images.

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Authors: Sai Munikoti, Ian Stewart, Chengping Chai, Lisa Linville, Scott Vasquez, Sameera Horawalavithana, Karl Pazdernik
Released: 2026-05-27 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because MULTISEISMO: A Multimodal Seismic Dataset and Model for Cross-Modal Seismic Understanding overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, text, under, eval, rate, model, absent. Source: arxiv cs.LG (Machine Learning).
arXiv: 2605.26320

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