4 citations · 11 across the 19 of their papers we have counts for
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cs.IR2024★ 1 cited
Language Representations Can be What Recommenders Need: Findings and Potentials
Leheng Sheng, An Zhang, Yi Zhang +3
Recent studies empirically indicate that language models (LMs) encode rich world knowledge beyond mere semantics, attracting significant attention across various fields. However, i…
cs.IR2024★ 4 cited
On Softmax Direct Preference Optimization for Recommendation
Yuxin Chen, Junfei Tan, An Zhang +5
Recommender systems aim to predict personalized rankings based on user preference data. With the rise of Language Models (LMs), LM-based recommenders have been widely explored due…