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From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference Enhancing Unsupervised Keyword Extraction in Academic Papers through Integrating Highlights with Abstract CAST: Modeling Semantic-Level Transitions for Complementary-Aware Sequential Recommendation IndiaFinBench: An Evaluation Benchmark for Large Language Model Performance on Indian Financial Regulatory Text Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility RARE: Redundancy-Aware Retrieval Evaluation Framework for High-Similarity Corpora Personalized Benchmarking: Evaluating LLMs by Individual Preferences Modular Representation Compression: Adapting LLMs for Efficient and Effective 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Benchmarking RAG and GraphRAG for Agentic Search Systems Hydra: Unifying Document Retrieval and Generation in a Single Vision-Language Model SocialWise: LLM-Agentic Conversation Therapy for Individuals with Autism Spectrum Disorder to Enhance Communication Skills Working Notes on Late Interaction Dynamics: Analyzing Targeted Behaviors of Late Interaction Models Resolving the Robustness-Precision Trade-off in Financial RAG through Hybrid Document-Routed Retrieval Spectral Tempering for Embedding Compression in Dense Passage Retrieval AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation To LLM, or Not to LLM: How Designers and Developers Navigate LLMs as Tools or Teammates A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection MSA: Memory Sparse Attention for Efficient End-to-End Memory Model Scaling to 100M Tokens From Verbatim to Gist: Distilling Pyramidal Multimodal Memory via Semantic Information Bottleneck for Long-Horizon Video Agents LiveGraph: Active-Structure Neural Re-ranking for Exercise Recommendation GaiaFlow: Semantic-Guided Diffusion Tuning for Carbon-Frugal Search Hunt Globally: Wide Search AI Agents for Drug Asset Scouting in Investing, Business Development, and Competitive Intelligence From Speech-to-Spatial: Grounding Utterances on A Live Shared View with Augmented Reality Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics Exploring Structural Complexity in Normative RAG with Graph-based approaches: A case study on the ETSI Standards SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Models MCERF: Advancing Multimodal LLM Evaluation of Engineering Documentation with Enhanced Retrieval SemaCDR: LLM-Powered Transferable Semantics for Cross-Domain Sequential Recommendation Beyond Offline A/B Testing: Context-Aware Agent Simulation for Recommender System Evaluation AI-assisted Protocol Information Extraction For Improved Accuracy and Efficiency in Clinical Trial Workflows Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning Retrieval-Augmented Large Language Models for Evidence-Informed Guidance on Cannabidiol Use in Older Adults RLPO: Residual Listwise Preference Optimization for Long-Context Review Ranking When & How to Write for Personalized Demand-aware Query Rewriting in Video Search Finch: Benchmarking Finance & Accounting across Spreadsheet-Centric Enterprise Workflows WisPaper: Your AI Scholar Search Engine GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs Hierarchical Semantic Retrieval with Cobweb WARBERT: A Hierarchical BERT-based Model for Web API Recommendation Reliable Evaluation Protocol for Low-Precision Retrieval VoteGCL: Enhancing Graph-based Recommendations with Majority-Voting LLM-Rerank Augmentation Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline Evaluation ProRank: Prompt Warmup via Reinforcement Learning for Small Language Models Reranking What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context From Limited Labels to Open Domains:An Efficient Learning Method for Drone-view Geo-Localization User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation PoTable: Towards Systematic Thinking via Plan-then-Execute Stage Reasoning on Tables An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs Auto-FP: An Experimental Study of Automated Feature Preprocessing for Tabular Data
Challenges in Search on Streaming Services: Netflix Case Study
Sudarshan Lamkhede, Sudeep Das · 2019-03-12 · via cs.IR updates on arXiv.org

We discuss salient challenges of building a search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the search context to aid content discovery and support searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level instant search experience, and the technical challenges associated with implementing it across different devices and languages for a global audience.

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