126 citations · 454 across the 39 of their papers we have counts for
39 papers
DAMA: Data- and Model-aware Alignment of Multi-modal LLMs
Jinda Lu, Junkang Wu, Jinghan Li +6
Direct Preference Optimization (DPO) has shown effectiveness in aligning multi-modal large language models (MLLM) with human preferences. However, existing methods exhibit an imbal…
A3S: A General Active Clustering Method with Pairwise Constraints
Xun Deng, Junlong Liu, Han Zhong +5
Active clustering aims to boost the clustering performance by integrating human-annotated pairwise constraints through strategic querying. Conventional approaches with semi-supervi…
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
Yang Zhang, Keqin Bao, Ming Yan +3
When adapting Large Language Models for Recommendation (LLMRec), it is crucial to integrate collaborative information. Existing methods achieve this by learning collaborative embed…
Large Language Models are Learnable Planners for Long-Term Recommendation
Wentao Shi, Xiangnan He, Yang Zhang +5
Planning for both immediate and long-term benefits becomes increasingly important in recommendation. Existing methods apply Reinforcement Learning (RL) to learn planning capacity b…
A Survey of Generative Search and Recommendation in the Era of Large Language Models
Yongqi Li, Xinyu Lin, Wenjie Wang +6
With the information explosion on the Web, search and recommendation are foundational infrastructures to satisfying users' information needs. As the two sides of the same coin, bot…
Exact and Efficient Unlearning for Large Language Model-based Recommendation
Zhiyu Hu, Yang Zhang, Minghao Xiao +3
The evolving paradigm of Large Language Model-based Recommendation (LLMRec) customizes Large Language Models (LLMs) through parameter-efficient fine-tuning (PEFT) using recommendat…