26 citations · 27 across the 12 of their papers we have counts for
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cs.LG2024
Adaptive Conditional Expert Selection Network for Multi-domain Recommendation
Kuiyao Dong, Xingyu Lou, Feng Liu +4
Mixture-of-Experts (MOE) has recently become the de facto standard in Multi-domain recommendation (MDR) due to its powerful expressive ability. However, such MOE-based method typic…
cs.IR2024
LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation
Bohao Wang, Feng Liu, Changwang Zhang +8
Sequential Recommenders generate recommendations based on users' historical interaction sequences. However, in practice, these collected sequences are often contaminated by noisy i…
cs.IR2024★ 26 cited
Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model
Yu Cui, Feng Liu, Pengbo Wang +5
Owing to their powerful semantic reasoning capabilities, Large Language Models (LLMs) have been effectively utilized as recommenders, achieving impressive performance. However, the…