{"list":"other","total":67,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"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":"2106.09685","title":"LoRA: Low-Rank Adaptation of Large Language Models","created":"2021-06-17","cited_by_count":14380},{"id":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"2305.18290","title":"Direct Preference Optimization: Your Language Model is Secretly a Reward Model","created":"2023-05-29","cited_by_count":8065},{"id":"1606.05250","title":"SQuAD: 100,000+ Questions for Machine Comprehension of Text","created":"2016-06-16","cited_by_count":4148},{"id":"2309.16609","title":"Qwen Technical Report","created":"2023-09-28","cited_by_count":3344},{"id":"1808.09781","title":"Self-Attentive Sequential Recommendation","created":"2018-08-20","cited_by_count":1184},{"id":"2409.12122","title":"Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement","created":"2024-09-18","cited_by_count":1090},{"id":"1904.06690","title":"BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer","created":"2019-04-14","cited_by_count":964},{"id":"1506.04757","title":"Image-based Recommendations on Styles and Substitutes","created":"2015-06-15","cited_by_count":706},{"id":"1511.06939","title":"Session-based Recommendations with Recurrent Neural Networks","created":"2015-11-21","cited_by_count":695},{"id":"1602.01585","title":"Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering","created":"2016-02-04","cited_by_count":520},{"id":"1809.07426","title":"Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding","created":"2018-09-19","cited_by_count":476},{"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":"2404.19737","title":"Better & Faster Large Language Models via Multi-token Prediction","created":"2024-04-30","cited_by_count":360},{"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":"2406.11931","title":"DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence","created":"2024-06-17","cited_by_count":331},{"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":"1702.01806","title":"Beam Search Strategies for Neural Machine Translation","created":"2017-02-06","cited_by_count":232},{"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":"2106.14226","title":"Sequential Recommendation with Graph Neural Networks","created":"2021-06-27","cited_by_count":89},{"id":"2404.14851","title":"From Matching to Generation: A Survey on Generative Information Retrieval","created":"2024-04-23","cited_by_count":89},{"id":"2308.08434","title":"A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems","created":"2023-08-16","cited_by_count":73},{"id":"2105.04170","title":"AutoDebias: Learning to Debias for Recommendation","created":"2021-05-10","cited_by_count":68},{"id":"2406.09215","title":"On Softmax Direct Preference Optimization for Recommendation","created":"2024-06-13","cited_by_count":64},{"id":"2312.02445","title":"LLaRA: Large Language-Recommendation Assistant","created":"2023-12-05","cited_by_count":56},{"id":"2207.05969","title":"Bootstrap Latent Representations for Multi-modal Recommendation","created":"2022-07-13","cited_by_count":55},{"id":"2305.06566","title":"ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models","created":"2023-05-11","cited_by_count":54},{"id":"2503.22675","title":"Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation","created":"2025-03-28","cited_by_count":51},{"id":"2404.11343","title":"Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System","created":"2024-04-17","cited_by_count":50},{"id":"2505.19092","title":"Reinforced Latent Reasoning for LLM-based Recommendation","created":"2025-05-25","cited_by_count":47},{"id":"2302.10632","title":"Multi-Modal Self-Supervised Learning for Recommendation","created":"2023-02-21","cited_by_count":45},{"id":"2201.02327","title":"On the Effectiveness of Sampled Softmax Loss for Item Recommendation","created":"2022-01-07","cited_by_count":39},{"id":"2311.09134","title":"Scalable and Effective Generative Information Retrieval","created":"2023-11-15","cited_by_count":39},{"id":"2306.00248","title":"TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest","created":"2023-05-31","cited_by_count":35},{"id":"2403.17688","title":"Large Language Models Enhanced Collaborative Filtering","created":"2024-03-26","cited_by_count":27},{"id":"2006.15408","title":"Learning Optimal Tree Models Under Beam Search","created":"2020-06-27","cited_by_count":26},{"id":"2403.00843","title":"Large Language Models are Learnable Planners for Long-Term Recommendation","created":"2024-02-29","cited_by_count":24},{"id":"2007.12000","title":"ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation","created":"2020-07-23","cited_by_count":22},{"id":"2404.12008","title":"How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective","created":"2024-04-18","cited_by_count":21},{"id":"2404.14600","title":"Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding","created":"2024-04-22","cited_by_count":19},{"id":"2412.09243","title":"SPRec: Self-Play to Debias LLM-based Recommendation","created":"2024-12-12","cited_by_count":18},{"id":"2402.12994","title":"Distributionally Robust Graph-based Recommendation System","created":"2024-02-20","cited_by_count":17},{"id":"2204.11165","title":"ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems","created":"2022-04-24","cited_by_count":13},{"id":"2405.00338","title":"Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model","created":"2024-05-01","cited_by_count":13},{"id":"2505.16865","title":"LARES: Latent Reasoning for Sequential Recommendation","created":"2025-05-22","cited_by_count":12},{"id":"2010.10789","title":"ProphetNet-Ads: A Looking Ahead Strategy for Generative Retrieval Models in Sponsored Search Engine","created":"2020-10-21","cited_by_count":11},{"id":"2404.07456","title":"WESE: Weak Exploration to Strong Exploitation for LLM Agents","created":"2024-04-11","cited_by_count":10},{"id":"2408.08208","title":"LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation","created":"2024-08-15","cited_by_count":10},{"id":"2504.04178","title":"MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender","created":"2025-04-05","cited_by_count":10},{"id":"2411.00163","title":"PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation","created":"2024-10-31","cited_by_count":9},{"id":"2508.05673","title":"Breaking the Top-$K$ Barrier: Advancing Top-$K$ Ranking Metrics Optimization in Recommender Systems","created":"2025-08-04","cited_by_count":9},{"id":"2410.22809","title":"Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation","created":"2024-10-30","cited_by_count":8},{"id":"2504.09935","title":"Constrained Auto-Regressive Decoding Constrains Generative Retrieval","created":"2025-04-14","cited_by_count":6},{"id":"2506.13229","title":"IGD: Token Decisiveness Modeling via Information Gain in LLMs for Personalized Recommendation","created":"2025-06-16","cited_by_count":5},{"id":"2510.10955","title":"HatLLM: Hierarchical Attention Masking for Enhanced Collaborative Modeling in LLM-based Recommendation","created":"2025-10-13","cited_by_count":5},{"id":"2505.14057","title":"Field Matters: A Lightweight LLM-enhanced Method for CTR Prediction","created":"2025-05-20","cited_by_count":4},{"id":"2311.05850","title":"Exploring Fine-tuning ChatGPT for News Recommendation","created":"2023-11-10","cited_by_count":3},{"id":"2601.21986","title":"SpecTran: Spectral-Aware Transformer-based Adapter for LLM-Enhanced Sequential Recommendation","created":"2026-01-29","cited_by_count":3},{"id":"2506.15120","title":"Advancing Loss Functions in Recommender Systems: A Comparative Study with a R\\'enyi Divergence-Based Solution","created":"2025-06-18","cited_by_count":2}],"next_cursor":null}