Movie Recommendation
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Benchmarks
MovieLens 1M
Most implemented
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
A Hybrid Variational Autoencoder for Collaborative Filtering
LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking
BloombergGPT: A Large Language Model for Finance
Training Compute-Optimal Large Language Models
Collaborative Filtering with Recurrent Neural Networks
Papers
Beyond Models: Reflections on Engineering AI-enabled Systems in a Project-Based Course
Teaching Software Engineering for AI-enabled systems entails addressing the integration of AI components within full-scale software architectures under realistic constraints. While machine learning courses emphasize mode…
Movie RecommendationEvaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation
The growing ubiquity of Extended Reality (XR) is driving Conversational Recommendation Systems (CRS) toward visually immersive experiences. We formalize this paradigm as Immersive CRS (ICRS), where recommended items are …
Recommendation SystemsMovie RecommendationUtilityMax Prompting: A Formal Framework for Multi-Objective Large Language Model Tasks
The success of a Large Language Model (LLM) task depends heavily on its prompt. Most use-cases specify prompts using natural language, which is inherently ambiguous when multiple objectives must be simultaneously satisfi…
Movie RecommendationDiagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations
Large language models (LLMs) and cross-encoder rerankers have gained attention for improving recommender systems, particularly in cold-start scenarios where user interaction history is limited. However, practical deploym…
Movie RecommendationAdaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items personalized to the user's preferences, but which also might get the user out of their comfort zo…
Movie RecommendationPoint ProcessesExplainRec: Towards Explainable Multi-Modal Zero-Shot Recommendation with Preference Attribution and Large Language Models
Recent advances in Large Language Models (LLMs) have opened new possibilities for recommendation systems, though current approaches such as TALLRec face challenges in explainability and cold-start scenarios. We present E…
Recommendation SystemsMovie RecommendationTransfer Learning