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Sequential recommendation aims to predict users' next interaction with items based on their past engagement sequence.
Curriculum learning. In ICML (ACM International Conference Proceeding Series, Vol. 382) . ACM, 41–48
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Language Models are Few-Shot Learners. In NeurIPS
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Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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Towards a Unified View of Parameter-Efficient Transfer Learning. In International Conference on Learning Representations
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The Power of Scale for Parameter-Efficient Prompt Tuning. In EMNLP (1) . Association for Computational Linguistics, 3045–3059
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Multimodal Few-Shot Learning with Frozen Language Models. In NeurIPS . 200–212
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Flamingo: a Visual Language Model for Few-Shot Learning. In NeurIPS
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M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems
Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang. 2022 · 2022
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Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). In RecSys . ACM, 299–315
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AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head
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A Critical Study on Data Leakage in Recommender System Offline Evaluation
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven C. H. Hoi. 2023a · 2023
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How Can Recommender Systems Benefit from Large Language Models: A Survey
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Towards Universal Sequence Representation Learning for Recommender Systems. In KDD . ACM, 585–593
Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, and Ji-Rong Wen. 2022 · 2022
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LoRA: Low-Rank Adaptation of Large Language Models. In ICLR . OpenReview.net
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. In ICLR . OpenReview.net
Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang, Jing Shao, Fengwei Yu, and Junjie Yan. 2022 · 2022
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Training language models to follow instructions with human feedback. In NeurIPS
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Large Language Models Encode Clinical Knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Scharli, Aakanksha Chowdhery, Philip Mansfield, Blaise Aguera y Arcas, Dale Webster, Greg S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle Barral, Christopher Semturs, Alan Karthikesalingam, and Vivek Natarajan. 2022 · 2022
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A Survey on Curriculum Learning
Xin Wang, Yudong Chen, and Wenwu Zhu. 2022 · 2022
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TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. In RecSys . ACM, 1007–1014
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He. 2023 · 2023
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Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
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Junling Liu, Chao Liu, Renjie Lv, Kang Zhou, and Yan Zhang. 2023b · 2023
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Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration
Chenyang Lyu, Minghao Wu, Longyue Wang, Xinting Huang, Bingshuai Liu, Zefeng Du, Shuming Shi, and Zhaopeng Tu. 2023 · 2023
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OpenAI. 2023 · 2023
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LLaMA: Open and Efficient Foundation Language Models
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A Survey on Large Language Models for Recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, and Enhong Chen. 2023b · 2023
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BloombergGPT: A Large Language Model for Finance
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A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. In SIGIR . ACM, 331–340
Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, and Xiang Wang. 2023 · 2023
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Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited. In SIGIR . ACM, 2639–2649
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni. 2023 · 2023
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Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
Hang Zhang, Xin Li, and Lidong Bing. 2023b · 2023
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CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation
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Minigpt-4: Enhancing vision-language understanding with advanced large language models
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Towards 3D Molecule-Text Interpretation in Language Models. In The Twelfth International Conference on Learning Representations
Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, and Qi Tian. 2024 · 2024
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On Generative Agents in Recommendation. In SIGIR
An Zhang, Yuxin Chen, Leheng Sheng, Xiang Wang, and Tat-Seng Chua. 2024 · 2024
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Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning. In SIGIR
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