8 citations · 20 across the 17 of their papers we have counts for
3 papers · 1 filter
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
Is Text All You Need? Text as a Universal Information Bottleneck for Speech LLMs
Ming-Hao Hsu, Yuxuan Hu, Shujie Liu +3
Large language models (LLMs) provide a powerful reasoning backbone for speech understanding, but integrating continuous acoustic signals into a pretrained LLM remains challenging.…
Closing the Modality Reasoning Gap for Speech Large Language Models
Chaoren Wang, Heng Lu, Xueyao Zhang +4
Although Speech Large Language Models have achieved notable progress, a substantial modality reasoning gap remains: their reasoning performance on speech inputs is markedly weaker…