{"list":"other","total":59,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396},{"id":"2203.02155","title":"Training language models to follow instructions with human feedback","created":"2022-03-04","cited_by_count":15971},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"2201.11903","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","created":"2022-01-28","cited_by_count":12459},{"id":"2306.05685","title":"Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena","created":"2023-06-09","cited_by_count":8626},{"id":"2204.02311","title":"PaLM: Scaling Language Modeling with Pathways","created":"2022-04-05","cited_by_count":5326},{"id":"2205.11916","title":"Large Language Models are Zero-Shot Reasoners","created":"2022-05-24","cited_by_count":4374},{"id":"1706.03741","title":"Deep reinforcement learning from human preferences","created":"2017-06-12","cited_by_count":3912},{"id":"1906.08237","title":"XLNet: Generalized Autoregressive Pretraining for Language Understanding","created":"2019-06-19","cited_by_count":2811},{"id":"2009.01325","title":"Learning to summarize from human feedback","created":"2020-09-02","cited_by_count":2588},{"id":"2303.18223","title":"A Survey of Large Language Models","created":"2023-03-31","cited_by_count":2576},{"id":"2107.13586","title":"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","created":"2021-07-28","cited_by_count":2234},{"id":"2202.03629","title":"Survey of Hallucination in Natural Language Generation","created":"2022-02-08","cited_by_count":2075},{"id":"2305.10403","title":"PaLM 2 Technical Report","created":"2023-05-17","cited_by_count":1162},{"id":"2002.02126","title":"LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation","created":"2020-02-06","cited_by_count":1139},{"id":"1708.05031","title":"Neural Collaborative Filtering","created":"2017-08-16","cited_by_count":1111},{"id":"2302.04023","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","created":"2023-02-08","cited_by_count":894},{"id":"1911.00536","title":"DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation","created":"2019-11-01","cited_by_count":842},{"id":"1612.08083","title":"Language Modeling with Gated Convolutional Networks","created":"2016-12-23","cited_by_count":702},{"id":"1511.06939","title":"Session-based Recommendations with Recurrent Neural Networks","created":"2015-11-21","cited_by_count":695},{"id":"2302.11382","title":"A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT","created":"2023-02-21","cited_by_count":619},{"id":"2203.13366","title":"Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)","created":"2022-03-24","cited_by_count":402},{"id":"2104.06599","title":"Learning How to Ask: Querying LMs with Mixtures of Soft Prompts","created":"2021-04-14","cited_by_count":377},{"id":"2302.09419","title":"A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT","created":"2023-02-18","cited_by_count":368},{"id":"2202.13169","title":"A Systematic Evaluation of Large Language Models of Code","created":"2022-02-26","cited_by_count":363},{"id":"2106.07139","title":"Pre-Trained Models: Past, Present and Future","created":"2021-06-14","cited_by_count":319},{"id":"2305.08845","title":"Large Language Models are Zero-Shot Rankers for Recommender Systems","created":"2023-05-15","cited_by_count":309},{"id":"2303.14524","title":"Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System","created":"2023-03-25","cited_by_count":242},{"id":"2308.07702","title":"Better Zero-Shot Reasoning with Role-Play Prompting","created":"2023-08-15","cited_by_count":223},{"id":"2304.10149","title":"Is ChatGPT a Good Recommender? A Preliminary Study","created":"2023-04-20","cited_by_count":193},{"id":"2305.07001","title":"Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach","created":"2023-05-11","cited_by_count":168},{"id":"2305.02182","title":"Uncovering ChatGPT's Capabilities in Recommender Systems","created":"2023-05-03","cited_by_count":161},{"id":"2205.08084","title":"M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems","created":"2022-05-17","cited_by_count":152},{"id":"2308.14296","title":"RecMind: Large Language Model Powered Agent For Recommendation","created":"2023-08-28","cited_by_count":129},{"id":"2308.10053","title":"Large Language Models as Zero-Shot Conversational Recommenders","created":"2023-08-19","cited_by_count":127},{"id":"2005.09683","title":"Neural Collaborative Filtering vs. Matrix Factorization Revisited","created":"2020-05-19","cited_by_count":123},{"id":"2305.06474","title":"Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction","created":"2023-05-10","cited_by_count":116},{"id":"2305.07609","title":"Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation","created":"2023-05-12","cited_by_count":114},{"id":"2106.11342","title":"Dive into Deep Learning","created":"2021-06-21","cited_by_count":111},{"id":"2304.03879","title":"GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation","created":"2023-04-08","cited_by_count":103},{"id":"1905.03375","title":"Embarrassingly Shallow Autoencoders for Sparse Data","created":"2019-05-08","cited_by_count":94},{"id":"1901.07555","title":"Managing Popularity Bias in Recommender Systems with Personalized Re-ranking","created":"2019-01-22","cited_by_count":82},{"id":"2202.07371","title":"Personalized Prompt Learning for Explainable Recommendation","created":"2022-02-15","cited_by_count":79},{"id":"2307.14225","title":"Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences","created":"2023-07-26","cited_by_count":66},{"id":"1911.07698","title":"A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research","created":"2019-11-18","cited_by_count":65},{"id":"2304.03153","title":"Zero-Shot Next-Item Recommendation using Large Pretrained Language Models","created":"2023-04-06","cited_by_count":53},{"id":"1301.7363","title":"Empirical Analysis of Predictive Algorithms for Collaborative Filtering","created":"2013-01-30","cited_by_count":47},{"id":"2210.14698","title":"Autoregressive Structured Prediction with Language Models","created":"2022-10-26","cited_by_count":43},{"id":"2308.07192","title":"gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling","created":"2023-08-14","cited_by_count":29},{"id":"2103.02590","title":"Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation","created":"2021-03-03","cited_by_count":28},{"id":"2305.15673","title":"BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model","created":"2023-05-25","cited_by_count":22},{"id":"2110.07477","title":"RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Models","created":"2021-10-14","cited_by_count":14},{"id":"2203.01155","title":"Top-N Recommendation Algorithms: A Quest for the State-of-the-Art","created":"2022-03-02","cited_by_count":12},{"id":"2209.01621","title":"Interactive Question Answering Systems: Literature Review","created":"2022-09-04","cited_by_count":7},{"id":"1903.11372","title":"Jaccard/Tanimoto similarity test and estimation methods","created":"2019-03-27","cited_by_count":4}],"next_cursor":null}