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Large language models (LLMs) have achieved remarkable success across various domains, but effectively incorporating complex and potentially noisy user timeline data into LLMs remains a challenge.
Language Models are Few-Shot Learners
Brown, T.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J. D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 1901
Earlier work this paper cites.
Learning dense representations for entity retrieval
Gillick, D.; Kulkarni, S.; Lansing, L.; Presta, A.; Baldridge, J.; Ie, E.; and Garcia-Olano, D. 2019 · 1909
Earlier work this paper cites.
Modeling task relationships in multi-task learning with multi-gate mixture-of-experts
Ma, J.; Zhao, Z.; Yi, X.; Chen, J.; Hong, L.; and Chi, E. H. 2018 · 1939
Earlier work this paper cites.
Scaling Laws for Neural Language Models
Kaplan, J.; McCandlish, S.; Henighan, T.; Brown, T. B.; Chess, B.; Child, R.; Gray, S.; Radford, A.; Wu, J.; and Amodei, D. 2020 · 2001
Earlier work this paper cites.
The MovieLens Datasets: History and Context
Harper, F. M.; and Konstan, J. A. 2015 · 2015
Earlier work this paper cites.
Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering
He, R.; and McAuley, J. 2016 · 2016
Earlier work this paper cites.
Length bias in encoder decoder models and a case for global conditioning
Sountsov, P.; and Sarawagi, S. 2016 · 2016
Earlier work this paper cites.
DropoutNet: Addressing Cold Start in Recommender Systems
Volkovs, M.; Yu, G. W.; and Poutanen, T. 2017 · 2017
Earlier work this paper cites.
Learning cross-lingual sentence representations via a multi-task dual-encoder model
Chidambaram, M.; Yang, Y.; Cer, D.; Yuan, S.; Sung, Y.-H.; Strope, B.; and Kurzweil, R. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. N. 2018 · 2018
Earlier work this paper cites.
End-to-end retrieval in continuous space
Gillick, D.; Presta, A.; and Tomar, G. S. 2018 · 2018
Earlier work this paper cites.
Learning Semantic Textual Similarity from Conversations
Yanga, Y.; Yuanc, S.; Cera, D.; Konga, S.-y.; Constanta, N.; Pilarc, P.; Gea, H.; Sunga, Y.-H.; Stropea, B.; and Kurzweila, R. 2018 · 2018
Earlier work this paper cites.
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
Sun, F.; Liu, J.; Wu, J.; Pei, C.; Lin, X.; Ou, W.; and Jiang, P. 2019 · 2019
Earlier work this paper cites.
Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations
Yi, X.; Yang, J.; Hong, L.; Cheng, D. Z.; Heldt, L.; Kumthekar, A. A.; Zhao, Z.; Wei, L.; and Chi, E., eds. 2019 · 2019
Earlier work this paper cites.
End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms
Jiang, J.-Y.; Wu, T.; Roumpos, G.; Cheng, H.-T.; Yi, X.; Chi, E.; Ganapathy, H.; Jindal, N.; Cao, P.; and Wang, W. 2020 · 2020
Earlier work this paper cites.
Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations
Yang, J.; Yi, X.; Zhiyuan Cheng, D.; Hong, L.; Li, Y.; Xiaoming Wang, S.; Xu, T.; and Chi, E. H. 2020 · 2020
Earlier work this paper cites.
Transformer Feed-Forward Layers Are Key-Value Memories
Geva, M.; Schuster, R.; Berant, J.; and Levy, O. 2021 · 2021
Earlier work this paper cites.
Perceiver: General perception with iterative attention
Jaegle, A.; Gimeno, F.; Brock, A.; Vinyals, O.; Zisserman, A.; and Carreira, J. 2021 · 2021
Earlier work this paper cites.
The Power of Scale for Parameter-Efficient Prompt Tuning
Lester, B.; Al-Rfou, R.; and Constant, N. 2021 · 2021
Earlier work this paper cites.
Learning Federated Representations and Recommendations with Limited Negatives
Ning, L.; Singhal, K.; Zhou, E. X.; and Prakash, S. 2021 · 2021
Earlier work this paper cites.
U-BERT: Pre-training User Representations for Improved Recommendation
Qiu, Z.; Wu, X.; Gao, J.; and Fan, W. 2021 · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
Earlier work this paper cites.
Self-Supervised Learning for Large-Scale Item Recommendations
Yao, T.; Yi, X.; Cheng, D. Z.; Yu, F.; Chen, T.; Menon, A.; Hong, L.; Chi, E. H.; Tjoa, S.; Kang, J. J.; and Ettinger, E. 2021 · 2021
Cited alongside, same era.
Flamingo: a visual language model for few-shot learning
Alayrac, J.-B.; Donahue, J.; Luc, P.; Miech, A.; Barr, I.; Hasson, Y.; Lenc, K.; Mensch, A.; Millican, K.; Reynolds, M.; et al. 2022 · 2022
Cited alongside, same era.
Intent Contrastive Learning for Sequential Recommendation
Chen, Y.; Liu, Z.; Li, J.; McAuley, J. J.; and Xiong, C. 2022b · 2022
Cited alongside, same era.
LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2022 · 2022
Cited alongside, same era.
Large Language Models are Zero-Shot Reasoners
Kojima, T.; Gu, S. S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y. 2022 · 2022
Cited alongside, same era.
UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining
How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections
Gu, A.; Johnson, I.; Timalsina, A.; Rudra, A.; and Ré, C. 2023 · 2023
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Onellm: One framework to align all modalities with language
Han, J.; Gong, K.; Zhang, Y.; Wang, J.; Zhang, K.; Lin, D.; Qiao, Y.; Gao, P.; and Yue, X. 2023 · 2023
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GenRec: Large Language Model for Generative Recommendation
Ji, J.; Li, Z.; Xu, S.; Hua, W.; Ge, Y.; Tan, J.; and Zhang, Y. 2023 · 2023
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Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction
Kang, W.-C.; Ni, J.; Mehta, N.; Sathiamoorthy, M.; Hong, L.; Chi, E.; and Cheng, D. Z. 2023 · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Li, J.; Shang, J.; and McAuley, J. 2022 · 2022
Cited alongside, same era.
Reed, S.; Zolna, K.; Parisotto, E.; Colmenarejo, S. G.; Novikov, A.; Barth-Maron, G.; Gimenez, M.; Sulsky, Y.; Kay, J.; Springenberg, J. T.; et al. 2022 · 2022
Cited alongside, same era.
Efficient Transformers: A Survey
Tay, Y.; Dehghani, M.; Bahri, D.; and Metzler, D. 2022 · 2022
Cited alongside, same era.
Contrastive learning for sequential recommendation
Xie, X.; Sun, F.; Liu, Z.; Wu, S.; Gao, J.; Zhang, J.; Ding, B.; and Cui, B. 2022 · 2022
Cited alongside, same era.
Coca: Contrastive captioners are image-text foundation models. arXiv 2022
Yu, J.; Wang, Z.; Vasudevan, V.; Yeung, L.; Seyedhosseini, M.; and Wu, Y. 2022 · 2022
Cited alongside, same era.
Anil, R.; Dai, A. M.; Firat, O.; Johnson, M.; Lepikhin, D.; Passos, A.; Shakeri, S.; Taropa, E.; Bailey, P.; Chen, Z.; et al. 2023 · 2023
Cited alongside, same era.
Basyal, L.; and Sanghvi, M. 2023 · 2023
Cited alongside, same era.
Li, R.; Deng, W.; Cheng, Y.; Yuan, Z.; Zhang, J.; and Yuan, F. 2023 · 2023
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Ring attention with blockwise transformers for near-infinite context
Liu, H.; Zaharia, M.; and Abbeel, P. 2023 · 2023
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LLM-Rec: Personalized Recommendation via Prompting Large Language Models
Lyu, H.; Jiang, S.; Zeng, H.; Wang, Q.; Zhang, S.; Chen, R.; Leung, C.; Tang, J.; Xia, Y.; and Luo, J. 2023 · 2023
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Anymal: An efficient and scalable any-modality augmented language model
Moon, S.; Madotto, A.; Lin, Z.; Nagarajan, T.; Smith, M.; Jain, S.; Yeh, C.-F.; Murugesan, P.; Heidari, P.; Liu, Y.; et al. 2023 · 2023
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Learning to compress prompts with gist tokens
Mu, J.; Li, X. L.; and Goodman, N. 2023 · 2023
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OpenAI. 2023 · 2023
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Generative Sequential Recommendation with GPTRec
Petrov, A. V.; and Macdonald, C. 2023 · 2023
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Llama 2: Open Foundation and Fine-Tuned Chat Models
Touvron, H.; Martin, L.; Stone, K.; Albert, P.; Almahairi, A.; Babaei, Y.; Bashlykov, N.; Batra, S.; Bhargava, P.; Bhosale, S.; Bikel, D.; Blecher, L.; Ferrer, C. C.; Chen, M.; Cucurull, G.; Esiobu, D.; Fernandes, J.; Fu, J.; Fu, W.; Fuller, B.; Gao, C.; Goswami, V.; Goyal, N.; Hartshorn, A.; Hosseini, S.; Hou, R.; Inan, H.; Kardas, M.; Kerkez, V.; Khabsa, M.; Kloumann, I.; Korenev, A.; Koura, P. S.; Lachaux, M.-A.; Lavril, T.; Lee, J.; Liskovich, D.; Lu, Y.; Mao, Y.; Martinet, X.; Mihaylov, T.; Mishra, P.; Molybog, I.; Nie, Y.; Poulton, A.; Reizenstein, J.; Rungta, R.; Saladi, K.; Schelten, A.; Silva, R.; Smith, E. M.; Subramanian, R.; Tan, X. E.; Tang, B.; Taylor, R.; Williams, A.; Kuan, J. X.; Xu, P.; Yan, Z.; Zarov, I.; Zhang, Y.; Fan, A.; Kambadur, M.; Narang, S.; Rodriguez, A.; Stojnic, R.; Edunov, S.; and Scialom, T. 2023 · 2023
Later among the works it cites.
Focused transformer: Contrastive training for context scaling
Tworkowski, S.; Staniszewski, K.; Pacek, M.; Wu, Y.; Michalewski, H.; and Miłoś, P. 2023 · 2023
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Augmenting Language Models with Long-Term Memory
Wang, W.; Dong, L.; Cheng, H.; Liu, X.; Yan, X.; Gao, J.; and Wei, F. 2023 · 2023
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Wei, J.; Wang, X.; Schuurmans, D.; Bosma, M.; Ichter, B.; Xia, F.; Chi, E.; Le, Q.; and Zhou, D. 2023 · 2023
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Automated Self-Supervised Learning for Recommendation
Xia, L.; Huang, C.; Huang, C.; Lin, K.; Yu, T.; and Kao, B. 2023 · 2023
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Retrieval meets long context large language models
Xu, P.; Ping, W.; Wu, X.; McAfee, L.; Zhu, C.; Liu, Z.; Subramanian, S.; Bakhturina, E.; Shoeybi, M.; and Catanzaro, B. 2023 · 2023
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OpenP5: Benchmarking Foundation Models for Recommendation
Xu, S.; Hua, W.; and Zhang, Y. 2023 · 2023
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Personalized Showcases: Generating multi-modal explanations for recommendations
Yan, A.; He, Z.; Li, J.; Zhang, T.; and McAuley, J. 2023 · 2023
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Debiased Contrastive Learning for Sequential Recommendation
Yang, Y.; Huang, C.; Xia, L.; Huang, C.; Luo, D.; and Lin, K. 2023 · 2023
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User Embedding Model for Personalized Language Prompting
Doddapaneni, S.; Sayana, K.; Jash, A.; Sodhi, S.; and Kuzmin, D. 2024 · 2024
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LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning
Jin, H.; Han, X.; Yang, J.; Jiang, Z.; Liu, Z.; Chang, C.-Y.; Chen, H.; and Hu, X. 2024 · 2024
Closest in time.