Search papers, labs, and topics across Lattice.
Pohang University of Science and Technology
3
0
6
9
LLMs waste context on redundant information when making recommendations; selectively augmenting only lesser-known items boosts accuracy and efficiency.
Achieve ensemble-level sequential recommendation performance with a single network at inference time by distilling diversity from a modular ensemble during training.
Naive fine-tuning of VLMs for multimodal sequential recommendation causes catastrophic modality collapse, but can be fixed with gradient rebalancing and cross-modal regularization.
