Reliability-aware Cross-sample Enhancement (RCE) is a framework for multimodal sentiment analysis that tackles noise and missing modalities by first applying an adaptive variational information bottleneck to compress unreliable modality information. It then retrieves high‑confidence, semantically consistent neighbors from a large candidate pool to enrich current representations, and finally fuses cross‑modal interactions through a multilevel reliability‑aware mechanism. Experiments show RCE consistently outperforms state‑of‑the‑art methods in full, noisy, and missing‑modality scenarios.
By Menghua Jiang, Haokai Gao, Xiangui Kang, Haifeng Hu, Sijie Mai
arXiv:2602. 08597v3 Announce Type: replace Abstract: Robust multimodal systems must remain effective when some modalities are noisy, degraded, or unreliable.
By Roland Bertin-Johannet, Lara Scipio, Leopold Mayti\'e, Rufin VanRullen
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By Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu, Vaidehi Patil
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By Ziheng Jia, Yingji Liang, Jiaying Qian, Xiongkuo Min
arXiv:2608. 03475v1 Announce Type: cross Abstract: Multimodal intent recognition combines linguistic, acoustic, and visual evidence, but individual modalities may be noisy, missing, semantically conflicting, or disproportionately dominant.
By Suraj Kumar, Mohnish Raj, Soumi Chattopadhayay, Chandranath Adak, Ayan Dutta