{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/recommendation-systems/papers/23","list_of":"/task/recommendation-systems","task":"Recommendation Systems","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":23,"pages_in_order":61,"rows_per_page":100,"rows":[2201,2300],"of":6047,"counts":{"archive_papers_tagged":6047,"with_a_code_link":1997,"where_syntology_ran_a_sample":330,"not_listed_spam_title":0,"listed":6047,"listed_where_code_ran":330,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":280,"every_run_a_failure_of_syntologys_instrument":50,"listed_with_a_run_with_no_instrument_failure":280,"listed_every_run_a_failure_of_syntologys_instrument":50,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/recommendation-systems","prev":"/task/recommendation-systems/papers/22","next":"/task/recommendation-systems/papers/24","papers":[{"url":null,"slug":"graph-structured-driven-dual-adaptation-for","title":"Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias","date":"2025-03-30","arxiv_id":"2503.23358","repositories_listed":0,"syntology":null},{"url":null,"slug":"ruleagent-discovering-rules-for","title":"RuleAgent: Discovering Rules for Recommendation Denoising with Autonomous Language Agents","date":"2025-03-30","arxiv_id":"2503.23374","repositories_listed":0,"syntology":null},{"url":null,"slug":"think-before-recommend-unleashing-the-latent","title":"Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation","date":"2025-03-28","arxiv_id":"2503.22675","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-personalized-conversational-sales","title":"Towards Personalized Conversational Sales Agents : Contextual User Profiling for Strategic Action","date":"2025-03-28","arxiv_id":"2504.08754","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-we-solving-a-well-defined-problem-a-task","title":"Are We Solving a Well-Defined Problem? A Task-Centric Perspective on Recommendation Tasks","date":"2025-03-27","arxiv_id":"2503.21188","repositories_listed":0,"syntology":null},{"url":null,"slug":"combigcn-an-effective-gcn-model-for","title":"CombiGCN: An effective GCN model for Recommender System","date":"2025-03-27","arxiv_id":"2503.21471","repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-qr-enhancing-fairness-aware-information","title":"FAIR-QR: Enhancing Fairness-aware Information Retrieval through Query Refinement","date":"2025-03-27","arxiv_id":"2503.21092","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-individual-to-group-developing-a-context","title":"From Individual to Group: Developing a Context-Aware Multi-Criteria Group Recommender System","date":"2025-03-27","arxiv_id":"2503.22752","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-on-the-design-of-a-short-video","title":"Research on the Design of a Short Video Recommendation System Based on Multimodal Information and Differential Privacy","date":"2025-03-27","arxiv_id":"2504.08751","repositories_listed":0,"syntology":null},{"url":null,"slug":"belightrec-a-lightweight-recommender-system","title":"BeLightRec: A lightweight recommender system enhanced with BERT","date":"2025-03-26","arxiv_id":"2503.20206","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-relevance-an-adaptive-exploration","title":"Beyond Relevance: An Adaptive Exploration-Based Framework for Personalized Recommendations","date":"2025-03-25","arxiv_id":"2503.19525","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-recommender-systems-using-textual","title":"Enhancing Recommender Systems Using Textual Embeddings from Pre-trained Language Models","date":"2025-03-24","arxiv_id":"2504.08746","repositories_listed":0,"syntology":null},{"url":null,"slug":"food-recommendation-with-balancing-comfort","title":"Food Recommendation With Balancing Comfort and Curiosity","date":"2025-03-24","arxiv_id":"2503.18355","repositories_listed":0,"syntology":null},{"url":null,"slug":"rau-towards-regularized-alignment-and","title":"RAU: Towards Regularized Alignment and Uniformity for Representation Learning in Recommendation","date":"2025-03-24","arxiv_id":"2503.18300","repositories_listed":0,"syntology":null},{"url":null,"slug":"frog-fair-removal-on-graphs","title":"FROG: Fair Removal on Graphs","date":"2025-03-23","arxiv_id":"2503.18197","repositories_listed":0,"syntology":null},{"url":null,"slug":"simulating-filter-bubble-on-short-video","title":"Simulating Filter Bubble on Short-video Recommender System with Large Language Model Agents","date":"2025-03-23","arxiv_id":"2504.08742","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiscale-contextual-bandits-for-long-term","title":"MultiScale Contextual Bandits for Long Term Objectives","date":"2025-03-22","arxiv_id":"2503.17674","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusion-augmented-graph-contrastive","title":"Diffusion-augmented Graph Contrastive Learning for Collaborative Filter","date":"2025-03-20","arxiv_id":"2503.16290","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-agentic-recommender-systems-in-the","title":"Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models","date":"2025-03-20","arxiv_id":"2503.16734","repositories_listed":0,"syntology":null},{"url":null,"slug":"ace-a-cardinality-estimator-for-set-valued","title":"ACE: A Cardinality Estimator for Set-Valued Queries","date":"2025-03-19","arxiv_id":"2503.14929","repositories_listed":0,"syntology":null},{"url":null,"slug":"rolling-forward-enhancing-lightgcn-with","title":"Rolling Forward: Enhancing LightGCN with Causal Graph Convolution for Credit Bond Recommendation","date":"2025-03-18","arxiv_id":"2503.14213","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-linearized-alternating-direction-multiplier","title":"A Linearized Alternating Direction Multiplier Method for Federated Matrix Completion Problems","date":"2025-03-17","arxiv_id":"2503.12733","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-the-dynamics-of-leadership-in","title":"Leveraging the Dynamics of Leadership in Group Recommendation Systems","date":"2025-03-17","arxiv_id":"2503.12877","repositories_listed":0,"syntology":null},{"url":null,"slug":"okra-an-explainable-heterogeneous-multi","title":"OKRA: an Explainable, Heterogeneous, Multi-Stakeholder Job Recommender System","date":"2025-03-17","arxiv_id":"2504.07108","repositories_listed":0,"syntology":null},{"url":null,"slug":"llmser-enhancing-sequential-recommendation","title":"LLMSeR: Enhancing Sequential Recommendation via LLM-based Data Augmentation","date":"2025-03-16","arxiv_id":"2503.12547","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-textual-collaborative-gap-through","title":"Bridging Textual-Collaborative Gap through Semantic Codes for Sequential Recommendation","date":"2025-03-15","arxiv_id":"2503.12183","repositories_listed":0,"syntology":null},{"url":null,"slug":"examples-as-the-prompt-a-scalable-approach","title":"Examples as the Prompt: A Scalable Approach for Efficient LLM Adaptation in E-Commerce","date":"2025-03-14","arxiv_id":"2503.13518","repositories_listed":0,"syntology":null},{"url":null,"slug":"muss-multilevel-subset-selection-for","title":"MUSS: Multilevel Subset Selection for Relevance and Diversity","date":"2025-03-14","arxiv_id":"2503.11126","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-feedback-loop-between-recommendation","title":"The Feedback Loop Between Recommendation Systems and Reactive Users","date":"2025-03-14","arxiv_id":"2504.07105","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-preference-aggregation","title":"Adaptive Preference Aggregation","date":"2025-03-13","arxiv_id":"2503.10215","repositories_listed":0,"syntology":null},{"url":null,"slug":"behavior-importance-aware-graph-neural","title":"Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation","date":"2025-03-11","arxiv_id":"2504.07102","repositories_listed":0,"syntology":null},{"url":null,"slug":"exposing-product-bias-in-llm-investment","title":"Exposing Product Bias in LLM Investment Recommendation","date":"2025-03-11","arxiv_id":"2503.08750","repositories_listed":0,"syntology":null},{"url":null,"slug":"alignpxtr-aligning-predicted-behavior","title":"AlignPxtr: Aligning Predicted Behavior Distributions for Bias-Free Video Recommendations","date":"2025-03-10","arxiv_id":"2503.06920","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-behavior-recommender-systems-a-survey","title":"Multi-Behavior Recommender Systems: A Survey","date":"2025-03-10","arxiv_id":"2503.06963","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-recommendation-models-in","title":"Personalized Recommendation Models in Federated Settings: A Survey","date":"2025-03-10","arxiv_id":"2504.07101","repositories_listed":0,"syntology":null},{"url":null,"slug":"reproducibility-and-artifact-consistency-of","title":"Reproducibility and Artifact Consistency of the SIGIR 2022 Recommender Systems Papers Based on Message Passing","date":"2025-03-10","arxiv_id":"2503.07823","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncovering-cross-domain-recommendation","title":"Uncovering Cross-Domain Recommendation Ability of Large Language Models","date":"2025-03-10","arxiv_id":"2503.07761","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-retrieval-augmented-llm-for","title":"Graph Retrieval-Augmented LLM for Conversational Recommendation Systems","date":"2025-03-09","arxiv_id":"2503.06430","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-is-all-you-need-towards-efficient-and","title":"Image is All You Need: Towards Efficient and Effective Large Language Model-Based Recommender Systems","date":"2025-03-08","arxiv_id":"2503.06238","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-llms-in-recommendation-tasks-a","title":"Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders","date":"2025-03-07","arxiv_id":"2503.05493","repositories_listed":0,"syntology":null},{"url":null,"slug":"matrix-factorization-for-inferring","title":"Matrix Factorization for Inferring Associations and Missing Links","date":"2025-03-06","arxiv_id":"2503.04680","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-free-graph-filtering-via-multimodal","title":"Training-Free Graph Filtering via Multimodal Feature Refinement for Extremely Fast Multimodal Recommendation","date":"2025-03-06","arxiv_id":"2503.04406","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoupled-recommender-systems-exploring","title":"Decoupled Recommender Systems: Exploring Alternative Recommender Ecosystem Designs","date":"2025-03-05","arxiv_id":"2503.03606","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-some-books-better-than-others","title":"Are some books better than others?","date":"2025-03-04","arxiv_id":"2503.02671","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-meets-dense-unified-generative","title":"Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations","date":"2025-03-04","arxiv_id":"2503.02453","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-explainable-doctor-recommendation","title":"Towards Explainable Doctor Recommendation with Large Language Models","date":"2025-03-04","arxiv_id":"2503.02298","repositories_listed":0,"syntology":null},{"url":null,"slug":"2503-01814","title":"LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation","date":"2025-03-03","arxiv_id":"2503.01814","repositories_listed":0,"syntology":null},{"url":null,"slug":"hi-series-algorithms-a-hybrid-of-substance","title":"HI-Series Algorithms A Hybrid of Substance Diffusion Algorithm and Collaborative Filtering","date":"2025-03-03","arxiv_id":"2503.01305","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-causal-transformer-with","title":"HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation","date":"2025-03-03","arxiv_id":"2503.01469","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-transfer-framework-for-enhancing-temporal","title":"A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings","date":"2025-03-02","arxiv_id":"2503.00852","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-conversational-recommender-system","title":"Federated Conversational Recommender System","date":"2025-03-02","arxiv_id":"2503.00999","repositories_listed":0,"syntology":null},{"url":null,"slug":"addressing-cold-start-problem-in-click","title":"Addressing Cold-start Problem in Click-Through Rate Prediction via Supervised Diffusion Modeling","date":"2025-03-01","arxiv_id":"2504.06270","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-parametric-batched-global-multi-armed","title":"Semi-Parametric Batched Global Multi-Armed Bandits with Covariates","date":"2025-03-01","arxiv_id":"2503.00565","repositories_listed":0,"syntology":null},{"url":null,"slug":"2502-21195","title":"Joint Modeling in Recommendations: A Survey","date":"2025-02-28","arxiv_id":"2502.21195","repositories_listed":0,"syntology":null},{"url":null,"slug":"seeing-eye-to-ai-applying-deep-feature-based","title":"Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization","date":"2025-02-28","arxiv_id":"2503.00228","repositories_listed":0,"syntology":null},{"url":null,"slug":"adage-active-defenses-against-gnn-extraction","title":"ADAGE: Active Defenses Against GNN Extraction","date":"2025-02-27","arxiv_id":"2503.00065","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-collaborative-filtering-based","title":"Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis","date":"2025-02-27","arxiv_id":"2503.00072","repositories_listed":0,"syntology":null},{"url":null,"slug":"recommendations-from-sparse-comparison-data","title":"Recommendations from Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization","date":"2025-02-27","arxiv_id":"2502.20033","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-106k-multi-topic-multilingual","title":"A 106K Multi-Topic Multilingual Conversational User Dataset with Emoticons","date":"2025-02-26","arxiv_id":"2502.19108","repositories_listed":0,"syntology":null},{"url":null,"slug":"onerec-unifying-retrieve-and-rank-with","title":"OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment","date":"2025-02-26","arxiv_id":"2502.18965","repositories_listed":0,"syntology":null},{"url":null,"slug":"pcl-prompt-based-continual-learning-for-user","title":"PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems","date":"2025-02-26","arxiv_id":"2502.19628","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-large-recommendation-models-via","title":"Training Large Recommendation Models via Graph-Language Token Alignment","date":"2025-02-26","arxiv_id":"2502.18757","repositories_listed":0,"syntology":null},{"url":null,"slug":"creator-side-recommender-system-challenges","title":"Creator-Side Recommender System: Challenges, Designs, and Applications","date":"2025-02-25","arxiv_id":"2502.20497","repositories_listed":0,"syntology":null},{"url":null,"slug":"unmasking-gender-bias-in-recommendation","title":"Unmasking Gender Bias in Recommendation Systems and Enhancing Category-Aware Fairness","date":"2025-02-25","arxiv_id":"2502.17921","repositories_listed":0,"syntology":null},{"url":null,"slug":"filterllm-text-to-distribution-llm-for","title":"FilterLLM: Text-To-Distribution LLM for Billion-Scale Cold-Start Recommendation","date":"2025-02-24","arxiv_id":"2502.16924","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-blessing-of-reasoning-llm-based","title":"The Blessing of Reasoning: LLM-Based Contrastive Explanations in Black-Box Recommender Systems","date":"2025-02-24","arxiv_id":"2502.16759","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-semantic-and-id-representation","title":"Unified Semantic and ID Representation Learning for Deep Recommenders","date":"2025-02-23","arxiv_id":"2502.16474","repositories_listed":0,"syntology":null},{"url":null,"slug":"esans-effective-and-semantic-aware-negative","title":"ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems","date":"2025-02-22","arxiv_id":"2502.16077","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-epistemic-uncertainty-in-cold","title":"Exploiting Epistemic Uncertainty in Cold-Start Recommendation Systems","date":"2025-02-22","arxiv_id":"2502.16256","repositories_listed":0,"syntology":null},{"url":null,"slug":"inference-computation-scaling-for-feature","title":"Inference Computation Scaling for Feature Augmentation in Recommendation Systems","date":"2025-02-22","arxiv_id":"2502.16040","repositories_listed":0,"syntology":null},{"url":null,"slug":"separated-contrastive-learning-for-matching","title":"Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling","date":"2025-02-22","arxiv_id":"2502.16239","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bert-based-hybrid-recommendation-system-for","title":"A BERT Based Hybrid Recommendation System For Academic Collaboration","date":"2025-02-21","arxiv_id":"2502.15223","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-query-product-relevance-labeling","title":"Automated Query-Product Relevance Labeling using Large Language Models for E-commerce Search","date":"2025-02-21","arxiv_id":"2502.15990","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-domain-gaps-between-pretrained","title":"Bridging Domain Gaps between Pretrained Multimodal Models and Recommendations","date":"2025-02-21","arxiv_id":"2502.15542","repositories_listed":0,"syntology":null},{"url":null,"slug":"coherency-improved-explainable-recommendation","title":"Coherency Improved Explainable Recommendation via Large Language Model","date":"2025-02-21","arxiv_id":"2504.05315","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-knowledge-selector-and-evaluator-for","title":"Dynamic Knowledge Selector and Evaluator for recommendation with Knowledge Graph","date":"2025-02-21","arxiv_id":"2502.15623","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-the-surface-uncovering-implicit","title":"Beyond the Surface: Uncovering Implicit Locations with LLMs for Personalized Local News","date":"2025-02-20","arxiv_id":"2502.14660","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-based-user-profile-management-for","title":"LLM-based User Profile Management for Recommender System","date":"2025-02-20","arxiv_id":"2502.14541","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-quantitative-language-for","title":"Multimodal Quantitative Language for Generative Recommendation","date":"2025-02-20","arxiv_id":"2504.05314","repositories_listed":0,"syntology":null},{"url":null,"slug":"breaking-the-clusters-uniformity-optimization","title":"Breaking the Clusters: Uniformity-Optimization for Text-Based Sequential Recommendation","date":"2025-02-19","arxiv_id":"2502.13530","repositories_listed":0,"syntology":null},{"url":null,"slug":"bursting-filter-bubble-enhancing-serendipity","title":"Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models","date":"2025-02-19","arxiv_id":"2502.13539","repositories_listed":0,"syntology":null},{"url":null,"slug":"continuous-k-max-bandits","title":"Continuous K-Max Bandits","date":"2025-02-19","arxiv_id":"2502.13467","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-large-recommendation-models","title":"Generative Large Recommendation Models: Emerging Trends in LLMs for Recommendation","date":"2025-02-19","arxiv_id":"2502.13783","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm4tag-automatic-tagging-system-for","title":"LLM4Tag: Automatic Tagging System for Information Retrieval via Large Language Models","date":"2025-02-19","arxiv_id":"2502.13481","repositories_listed":0,"syntology":null},{"url":null,"slug":"talkplay-multimodal-music-recommendation-with","title":"TALKPLAY: Multimodal Music Recommendation with Large Language Models","date":"2025-02-19","arxiv_id":"2502.13713","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-sim-to-real-methods-in-rl","title":"A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Models","date":"2025-02-18","arxiv_id":"2502.13187","repositories_listed":0,"syntology":null},{"url":null,"slug":"envious-explore-and-exploit","title":"Envious Explore and Exploit","date":"2025-02-18","arxiv_id":"2502.12798","repositories_listed":0,"syntology":null},{"url":null,"slug":"fragility-aware-classification-for","title":"Fragility-aware Classification for Understanding Risk and Improving Generalization","date":"2025-02-18","arxiv_id":"2502.13024","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-principles-to-applications-a","title":"From Principles to Applications: A Comprehensive Survey of Discrete Tokenizers in Generation, Comprehension, Recommendation, and Information Retrieval","date":"2025-02-18","arxiv_id":"2502.12448","repositories_listed":0,"syntology":null},{"url":null,"slug":"introducing-context-information-in-lifelong","title":"Context-Aware Lifelong Sequential Modeling for Online Click-Through Rate Prediction","date":"2025-02-18","arxiv_id":"2502.12634","repositories_listed":0,"syntology":null},{"url":null,"slug":"preventing-the-popular-item-embedding-based","title":"Preventing the Popular Item Embedding Based Attack in Federated Recommendations","date":"2025-02-18","arxiv_id":"2502.12958","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertain-multi-objective-recommendation-via","title":"Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization","date":"2025-02-18","arxiv_id":"2502.13180","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-recommendation-explanations-through","title":"Enhancing Recommendation Explanations through User-Centric Refinement","date":"2025-02-17","arxiv_id":"2502.11721","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-generations-from-ai-1-0-to-ai-4-0","title":"AI Generations: From AI 1.0 to AI 4.0","date":"2025-02-16","arxiv_id":"2502.11312","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-llm-powered-agents-for","title":"A Survey on LLM-powered Agents for Recommender Systems","date":"2025-02-14","arxiv_id":"2502.10050","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-efficient-large-recommendation-model","title":"An Efficient Large Recommendation Model: Towards a Resource-Optimal Scaling Law","date":"2025-02-14","arxiv_id":"2502.09888","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-the-rationality-of-ai-decision","title":"Benchmarking the rationality of AI decision making using the transitivity axiom","date":"2025-02-14","arxiv_id":"2502.10554","repositories_listed":0,"syntology":null},{"url":null,"slug":"combinatorial-reinforcement-learning-with","title":"Combinatorial Reinforcement Learning with Preference Feedback","date":"2025-02-14","arxiv_id":"2502.10158","repositories_listed":0,"syntology":null},{"url":null,"slug":"proreco-a-process-discovery-recommender","title":"ProReco: A Process Discovery Recommender System","date":"2025-02-14","arxiv_id":"2502.10230","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-llm-based-news-recommender","title":"A Survey on LLM-based News Recommender Systems","date":"2025-02-13","arxiv_id":"2502.09797","repositories_listed":0,"syntology":null}],"record_sha256":"ad791c47cd167ceb88b066ed97776c8749310f8b170f95ea7c44241807190cc6","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}