{"list":"other","total":111,"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":"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":"2106.09685","title":"LoRA: Low-Rank Adaptation of Large Language Models","created":"2021-06-17","cited_by_count":14380},{"id":"2201.11903","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","created":"2022-01-28","cited_by_count":12459},{"id":"1910.13461","title":"BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension","created":"2019-10-29","cited_by_count":5893},{"id":"2203.11171","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","created":"2022-03-21","cited_by_count":5708},{"id":"2204.02311","title":"PaLM: Scaling Language Modeling with Pathways","created":"2022-04-05","cited_by_count":5326},{"id":"1902.00751","title":"Parameter-Efficient Transfer Learning for NLP","created":"2019-02-02","cited_by_count":4236},{"id":"2109.01652","title":"Finetuned Language Models Are Zero-Shot Learners","created":"2021-09-03","cited_by_count":3780},{"id":"2303.18223","title":"A Survey of Large Language Models","created":"2023-03-31","cited_by_count":2576},{"id":"2012.07805","title":"Extracting Training Data from Large Language Models","created":"2020-12-14","cited_by_count":2189},{"id":"2202.03629","title":"Survey of Hallucination in Natural Language Generation","created":"2022-02-08","cited_by_count":2075},{"id":"2012.15723","title":"Making Pre-trained Language Models Better Few-shot Learners","created":"2020-12-31","cited_by_count":1256},{"id":"2201.08239","title":"LaMDA: Language Models for Dialog Applications","created":"2022-01-20","cited_by_count":1220},{"id":"2002.02126","title":"LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation","created":"2020-02-06","cited_by_count":1139},{"id":"1806.01973","title":"Graph Convolutional Neural Networks for Web-Scale Recommender Systems","created":"2018-06-06","cited_by_count":1138},{"id":"1708.05031","title":"Neural Collaborative Filtering","created":"2017-08-16","cited_by_count":1111},{"id":"1904.06690","title":"BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer","created":"2019-04-14","cited_by_count":964},{"id":"2203.14465","title":"STaR: Bootstrapping Reasoning With Reasoning","created":"2022-03-28","cited_by_count":940},{"id":"2303.17564","title":"BloombergGPT: A Large Language Model for Finance","created":"2023-03-30","cited_by_count":939},{"id":"2303.08896","title":"SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models","created":"2023-03-15","cited_by_count":810},{"id":"1902.07243","title":"Graph Neural Networks for Social Recommendation","created":"2019-02-19","cited_by_count":714},{"id":"1511.06939","title":"Session-based Recommendations with Recurrent Neural Networks","created":"2015-11-21","cited_by_count":695},{"id":"2112.08633","title":"Learning To Retrieve Prompts for In-Context Learning","created":"2021-12-16","cited_by_count":648},{"id":"1909.11059","title":"Unified Vision-Language Pre-Training for Image Captioning and VQA","created":"2019-09-24","cited_by_count":494},{"id":"2011.02260","title":"Graph Neural Networks in Recommender Systems: A Survey","created":"2020-11-04","cited_by_count":494},{"id":"2111.01243","title":"Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey","created":"2021-11-01","cited_by_count":463},{"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":"2305.19860","title":"A Survey on Large Language Models for Recommendation","created":"2023-05-31","cited_by_count":379},{"id":"2305.00447","title":"TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation","created":"2023-04-30","cited_by_count":337},{"id":"2305.08845","title":"Large Language Models are Zero-Shot Rankers for Recommender Systems","created":"2023-05-15","cited_by_count":309},{"id":"2306.06031","title":"FinGPT: Open-Source Financial Large Language Models","created":"2023-06-09","cited_by_count":253},{"id":"2303.14524","title":"Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System","created":"2023-03-25","cited_by_count":242},{"id":"2010.03240","title":"Bias and Debias in Recommender System: A Survey and Future Directions","created":"2020-10-07","cited_by_count":240},{"id":"2305.15075","title":"HuatuoGPT, towards Taming Language Model to Be a Doctor","created":"2023-05-24","cited_by_count":214},{"id":"2305.05065","title":"Recommender Systems with Generative Retrieval","created":"2023-05-08","cited_by_count":198},{"id":"2304.10149","title":"Is ChatGPT a Good Recommender? A Preliminary Study","created":"2023-04-20","cited_by_count":193},{"id":"2101.06286","title":"Reinforcement learning based recommender systems: A survey","created":"2021-01-15","cited_by_count":188},{"id":"2305.14552","title":"Sources of Hallucination by Large Language Models on Inference Tasks","created":"2023-05-23","cited_by_count":169},{"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":"2109.12843","title":"A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions","created":"2021-09-27","cited_by_count":144},{"id":"2306.05817","title":"How Can Recommender Systems Benefit from Large Language Models: A Survey","created":"2023-06-09","cited_by_count":142},{"id":"2304.01097","title":"DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task","created":"2023-04-03","cited_by_count":131},{"id":"2303.13835","title":"Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited","created":"2023-03-24","cited_by_count":124},{"id":"2206.05941","title":"Towards Universal Sequence Representation Learning for Recommender Systems","created":"2022-06-13","cited_by_count":121},{"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":"2210.12316","title":"Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders","created":"2022-10-22","cited_by_count":112},{"id":"1905.04413","title":"Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems","created":"2019-05-11","cited_by_count":107},{"id":"2304.03879","title":"GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation","created":"2023-04-08","cited_by_count":103},{"id":"2206.03761","title":"A Survey on the Fairness of Recommender Systems","created":"2022-06-08","cited_by_count":102},{"id":"2305.06569","title":"How to Index Item IDs for Recommendation Foundation Models","created":"2023-05-11","cited_by_count":102},{"id":"2305.07622","title":"PALR: Personalization Aware LLMs for Recommendation","created":"2023-05-12","cited_by_count":96},{"id":"2107.06641","title":"Trustworthy AI: A Computational Perspective","created":"2021-07-12","cited_by_count":93},{"id":"2306.06615","title":"Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective","created":"2023-06-11","cited_by_count":92},{"id":"1910.10486","title":"Does Gender Matter? Towards Fairness in Dialogue Systems","created":"2019-10-16","cited_by_count":89},{"id":"2206.09363","title":"Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning","created":"2022-06-19","cited_by_count":86},{"id":"1701.04783","title":"Joint Deep Modeling of Users and Items Using Reviews for Recommendation","created":"2017-01-17","cited_by_count":84},{"id":"2306.15546","title":"When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions","created":"2023-06-27","cited_by_count":84},{"id":"2302.02591","title":"Generative Diffusion Models on Graphs: Methods and Applications","created":"2023-02-06","cited_by_count":81},{"id":"2304.11116","title":"Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT","created":"2023-04-10","cited_by_count":80},{"id":"2305.11255","title":"Reasoning Implicit Sentiment with Chain-of-Thought Prompting","created":"2023-05-18","cited_by_count":80},{"id":"2202.07371","title":"Personalized Prompt Learning for Explainable Recommendation","created":"2022-02-15","cited_by_count":79},{"id":"2306.10933","title":"Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models","created":"2023-06-19","cited_by_count":74},{"id":"2304.03516","title":"Generative Recommendation: Towards Next-generation Recommender Paradigm","created":"2023-04-07","cited_by_count":70},{"id":"2206.08082","title":"Self-Generated In-Context Learning: Leveraging Auto-regressive Language Models as a Demonstration Generator","created":"2022-06-16","cited_by_count":68},{"id":"2305.07961","title":"Leveraging Large Language Models in Conversational Recommender Systems","created":"2023-05-13","cited_by_count":63},{"id":"2307.00457","title":"GenRec: Large Language Model for Generative Recommendation","created":"2023-07-02","cited_by_count":63},{"id":"2305.15062","title":"Lawyer LLaMA Technical Report","created":"2023-05-24","cited_by_count":54},{"id":"2108.05552","title":"Graph Trend Filtering Networks for Recommendations","created":"2021-08-12","cited_by_count":53},{"id":"2304.03153","title":"Zero-Shot Next-Item Recommendation using Large Pretrained Language Models","created":"2023-04-06","cited_by_count":53},{"id":"2305.13112","title":"Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models","created":"2023-05-22","cited_by_count":48},{"id":"2002.11252","title":"AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations","created":"2020-02-26","cited_by_count":47},{"id":"2302.05729","title":"A Brief Report on LawGPT 1.0: A Virtual Legal Assistant Based on GPT-3","created":"2023-02-11","cited_by_count":46},{"id":"2302.03735","title":"Pre-train, Prompt and Recommendation: A Comprehensive Survey of Language Modelling Paradigm Adaptations in Recommender Systems","created":"2023-02-07","cited_by_count":45},{"id":"2305.06212","title":"Privacy-Preserving Parameter-Efficient Fine-Tuning for Large Language Model Services","created":"2023-05-10","cited_by_count":43},{"id":"2305.17812","title":"Tab-CoT: Zero-shot Tabular Chain of Thought","created":"2023-05-28","cited_by_count":42},{"id":"2305.11700","title":"Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights","created":"2023-05-19","cited_by_count":38},{"id":"2305.12090","title":"UP5: Unbiased Foundation Model for Fairness-aware Recommendation","created":"2023-05-20","cited_by_count":38},{"id":"2209.10222","title":"Fairness Reprogramming","created":"2022-09-21","cited_by_count":33},{"id":"1907.06853","title":"Deep Social Collaborative Filtering","created":"2019-07-16","cited_by_count":32},{"id":"2204.06923","title":"A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems","created":"2022-04-14","cited_by_count":32},{"id":"2209.10117","title":"A Comprehensive Survey on Trustworthy Recommender Systems","created":"2022-09-21","cited_by_count":32},{"id":"2005.08147","title":"Attacking Black-box Recommendations via Copying Cross-domain User Profiles","created":"2020-05-17","cited_by_count":31},{"id":"2106.06713","title":"AutoLoss: Automated Loss Function Search in Recommendations","created":"2021-06-12","cited_by_count":31},{"id":"2306.02250","title":"Large Language Model Augmented Narrative Driven Recommendations","created":"2023-06-04","cited_by_count":31},{"id":"1607.07326","title":"Meta-Prod2Vec - Product Embeddings Using Side-Information for Recommendation","created":"2016-07-25","cited_by_count":30},{"id":"2106.08934","title":"Personalized News Recommendation: Methods and Challenges","created":"2021-06-16","cited_by_count":30},{"id":"2305.15036","title":"Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights","created":"2023-05-24","cited_by_count":29},{"id":"1809.07062","title":"Adversarial Training Towards Robust Multimedia Recommender System","created":"2018-09-19","cited_by_count":28},{"id":"2206.06190","title":"TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback","created":"2022-06-13","cited_by_count":27},{"id":"2208.08723","title":"Disentangled Contrastive Learning for Social Recommendation","created":"2022-08-18","cited_by_count":27},{"id":"2207.10307","title":"Knowledge-enhanced Black-box Attacks for Recommendations","created":"2022-07-21","cited_by_count":26},{"id":"2305.09858","title":"Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs","created":"2023-05-17","cited_by_count":24},{"id":"2305.15498","title":"Large Language Models for User Interest Journeys","created":"2023-05-24","cited_by_count":24}],"next_cursor":"100"}