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cs.SD2026
PLACE: Positional Latent Adaptation via Conditioned Embeddings for Binaural Audio Generation
Tiernon Riesenmy, You Zhang, Gautam Bhattacharya +1
We present PLACE, a method that extends the pretrained any-to-audio model AudioX for binaural generation from arbitrary combinations of text, video, and optional audio prompts. PLA…
cs.LG2026
Decomposing multimodal embedding spaces with group-sparse autoencoders
Chiraag Kaushik, Davis Barch, Andrea Fanelli
The Linear Representation Hypothesis asserts that the embeddings learned by neural networks can be understood as linear combinations of features corresponding to high-level concept…