6 citations · 6 across the 6 of their papers we have counts for
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cs.IR2026
RankGR: Rank-Enhanced Generative Retrieval with Listwise Direct Preference Optimization in Recommendation
Kairui Fu, Changfa Wu, Kun Yuan +8
Generative retrieval (GR) has emerged as a promising paradigm in recommendation systems by autoregressively decoding identifiers of target items. Despite its potential, current app…
cs.IR2026
MALLOC: Benchmarking the Memory-aware Long Sequence Compression for Large Sequential Recommendation
Qihang Yu, Kairui Fu, Zhaocheng Du +10
The scaling law, which indicates that model performance improves with increasing dataset and model capacity, has fueled a growing trend in expanding recommendation models in both i…
cs.IR2025★ 6 cited
Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation
Zheqi Lv, Tianyu Zhan, Wenjie Wang +6
Large Language Models (LLMs) for Recommendation (LLM4Rec) is a promising research direction that has demonstrated exceptional performance in this field. However, its inability to c…