#Recommendation Systems
Latest news articles tagged with "Recommendation Systems". Follow the timeline of events, related topics, and entities.
Articles (13)
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🇺🇸 Interplay: Training Independent Simulators for Reference-Free Conversational Recommendation
[USA]
arXiv:2603.18573v1 Announce Type: new Abstract: Training conversational recommender systems (CRS) requires extensive dialogue data, which is challenging to collect at scale. To address this, research...
Related: #Conversational AI -
🇺🇸 VLM2Rec: Resolving Modality Collapse in Vision-Language Model Embedders for Multimodal Sequential Recommendation
[USA]
arXiv:2603.17450v1 Announce Type: cross Abstract: Sequential Recommendation (SR) in multimodal settings typically relies on small frozen pretrained encoders, which limits semantic capacity and preven...
Related: #AI Research -
🇺🇸 Entropy Guided Diversification and Preference Elicitation in Agentic Recommendation Systems
[USA]
arXiv:2603.11399v1 Announce Type: new Abstract: Users on e-commerce platforms can be uncertain about their preferences early in their search. Queries to recommendation systems are frequently ambiguou...
Related: #AI Personalization -
🇺🇸 Isotonic Layer: A Universal Framework for Generic Recommendation Debiasing
[USA]
arXiv:2603.06589v1 Announce Type: cross Abstract: Model calibration and debiasing are fundamental to the reliability and fairness of large scale recommendation systems. We introduce the Isotonic Laye...
Related: #Algorithmic Bias -
🇺🇸 Exploration Space Theory: Formal Foundations for Prerequisite-Aware Location-Based Recommendation
[USA]
arXiv:2603.06624v1 Announce Type: cross Abstract: Location-based recommender systems have achieved considerable sophistication, yet none provides a formal, lattice-theoretic representation of prerequ...
Related: #Location-Based Services -
🇺🇸 Debiasing Sequential Recommendation with Time-aware Inverse Propensity Scoring
[USA]
arXiv:2603.04986v1 Announce Type: cross Abstract: Sequential Recommendation (SR) predicts users next interactions by modeling the temporal order of their historical behaviors. Existing approaches, in...
Related: #Bias Mitigation -
🇺🇸 Generative Data Transformation: From Mixed to Unified Data
[USA]
arXiv:2602.22743v1 Announce Type: new Abstract: Recommendation model performance is intrinsically tied to the quality, volume, and relevance of their training data. To address common challenges like ...
Related: #Artificial Intelligence, #Data Science -
🇺🇸 From Logs to Language: Learning Optimal Verbalization for LLM-Based Recommendation in Production
[USA]
arXiv:2602.20558v1 Announce Type: new Abstract: Large language models (LLMs) are promising backbones for generative recommender systems, yet a key challenge remains underexplored: verbalization, i.e....
Related: #Artificial Intelligence, #Natural Language Processing -
🇺🇸 Conv-FinRe: A Conversational and Longitudinal Benchmark for Utility-Grounded Financial Recommendation
[USA]
arXiv:2602.16990v1 Announce Type: new Abstract: Most recommendation benchmarks evaluate how well a model imitates user behavior. In financial advisory, however, observed actions can be noisy or short...
Related: #Artificial Intelligence, #Financial Recommendation, #Large Language Models, #Conversational AI -
🇺🇸 Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System
[USA]
arXiv:2602.16124v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search is widely used in the retrieval stage of large-scale recommendation systems. In this stage, candidate items...
Related: #Artificial Intelligence Research, #Approximate Nearest Neighbor Search, #Indexing Strategies, #Embedding Learning -
🇺🇸 Enhancing guidance for missing data in diffusion-based sequential recommendation
[USA]
arXiv:2601.15673v2 Announce Type: replace-cross Abstract: Contemporary sequential recommendation methods are becoming more complex, shifting from classification to a diffusion-guided generative parad...
Related: #Artificial Intelligence, #Data Quality -
🇺🇸 Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation
[USA]
arXiv:2602.07298v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) represent a promising frontier for recommender systems, yet their development has been impeded by the absence of...
Related: #Machine Learning, #Scaling Laws, #Synthetic Data -
🇺🇸 RGAlign-Rec: Ranking-Guided Alignment for Latent Query Reasoning in Recommendation Systems
[USA]
arXiv:2602.12968v1 Announce Type: cross Abstract: Proactive intent prediction is a critical capability in modern e-commerce chatbots, enabling "zero-query" recommendations by anticipating user needs ...
Related: #Natural Language Processing, #E-commerce Technology
Key Entities (5)
- Large language model (2 news)
- Reinforcement learning (1 news)
- Verbalisation (1 news)
- Resource allocation (1 news)
- Tel Aviv Stock Exchange (1 news)
About the topic: Recommendation Systems
The topic "Recommendation Systems" aggregates 13+ news articles from various countries.