Fetching the paper…
Reading the bibliography…
Long-text generation is seemingly ubiquitous in real-world applications of large language models such as generating an email or writing a review.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2019 · 1904
Earlier work this paper cites.
Towards controllable and personalized review generation
Pan Li and Alexander Tuzhilin. 2019 · 1910
Earlier work this paper cites.
Okapi at trec-3
Stephen Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford. 1994 · 1994
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
Earlier work this paper cites.
Avocado research email collection ldc2015t03
Douglas Oard et al. 2015 · 2015
Earlier work this paper cites.
Beam search strategies for neural machine translation
Markus Freitag and Yaser Al-Onaizan. 2017 · 2017
Earlier work this paper cites.
Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
Earlier work this paper cites.
Tl;dr: Mining reddit to learn automatic summarization
Michael Völske, Martin Potthast, Shahbaz Syed, and Benno Stein. 2017 · 2017
Earlier work this paper cites.
Training millions of personalized dialogue agents
Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison, and Antoine Bordes. 2018 · 2018
Earlier work this paper cites.
Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018 · 2018
Earlier work this paper cites.
The secret sharer: Evaluating and testing unintended memorization in neural networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song. 2019 · 2019
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Cited alongside, same era.
Justifying recommendations using distantly-labeled reviews and fine-grained aspects
Jianmo Ni, Jiacheng Li, and Julian McAuley. 2019 · 2019
Cited alongside, same era.
Knowledge-enhanced personalized review generation with capsule graph neural network
Junyi Li, Siqing Li, Wayne Xin Zhao, Gaole He, Zhicheng Wei, Nicholas Jing Yuan, and Ji-Rong Wen. 2020 · 2020
Cited alongside, same era.
When does text prediction benefit from additional context? an exploration of contextual signals for chat and email messages
Stojan Trajanovski, Chad Atalla, Kunho Kim, Vipul Agarwal, Milad Shokouhi, and Chris Quirk. 2021 · 2021
Cited alongside, same era.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei. 2022 · 2022
Teach llms to personalize–an approach inspired by writing education
Cheng Li, Mingyang Zhang, Qiaozhu Mei, Yaqing Wang, Spurthi Amba Hombaiah, Yi Liang, and Michael Bendersky. 2023 · 2023
Later among the works it cites.
Lost in the middle: How language models use long contexts
Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2023 · 2023
Later among the works it cites.
The flan collection: Designing data and methods for effective instruction tuning
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V Le, Barret Zoph, Jason Wei, et al. 2023 · 2023
Later among the works it cites.
Pearl: Personalizing large language model writing assistants with generation-calibrated retrievers
Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, and Tara Safavi. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Learning to transfer prompts for text generation
Junyi Li, Tianyi Tang, Jian-Yun Nie, Ji-Rong Wen, and Xin Zhao. 2022 · 2022
Cited alongside, same era.
UserIdentifier: Implicit user representations for simple and effective personalized sentiment analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, and Dimitrios Dimitriadis. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Cited alongside, same era.
A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung. 2023 · 2023
Cited alongside, same era.
Sentiment analysis for personalized chatbots in e-commerce applications
Anas El-Ansari and Abderrahim Beni-Hssane. 2023 · 2023
Cited alongside, same era.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
Cited alongside, same era.
Unsupervised dense retrieval with relevance-aware contrastive pre-training
Yibin Lei, Liang Ding, Yu Cao, Changtong Zan, Andrew Yates, and Dacheng Tao. 2023 · 2023
Cited alongside, same era.
Alireza Salemi, Sheshera Mysore, Michael Bendersky, and Hamed Zamani. 2023 · 2023
Later among the works it cites.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
Later among the works it cites.
Personalized text generation with fine-grained linguistic control
Bashar Alhafni, Vivek Kulkarni, Dhruv Kumar, and Vipul Raheja. 2024b · 2024
Closest in time.
Learning to rewrite prompts for personalized text generation
Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, and Michael Bendersky. 2024 · 2024
Closest in time.
A rag chatbot for precision medicine of multiple myeloma
Mujahid Ali Quidwai and Alessandro Lagana. 2024 · 2024
Closest in time.
Optimization methods for personalizing large language models through retrieval augmentation
Alireza Salemi, Surya Kallumadi, and Hamed Zamani. 2024 · 2024
Closest in time.
Unims-rag: A unified multi-source retrieval-augmented generation for personalized dialogue systems
Hongru Wang, Wenyu Huang, Yang Deng, Rui Wang, Zezhong Wang, Yufei Wang, Fei Mi, Jeff Z Pan, and Kam-Fai Wong. 2024 · 2024
Closest in time.