Applied & Human-Centered · Computer Science & AI
Information Retrieval
The newest papers in Information Retrieval that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
979 papers, from 4 September 2026 to 5 November 2026: 979 arXiv preprints.
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Newest papers, page 28
Generate What You Can Trust: Content Credibility in Generative Recommenders
Generative recommendation (GR) represents items with semantic IDs (i.e., discrete token sequences) and generates target item tokens as recommendations.Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based Prompts
Large language models (LLMs) are increasingly used for literature search and synthesis.PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents
LLM agents rely on long-term memory to retain and reuse information when performing tasks over long horizons.Beyond Semantic Similarity: Performance and Costs of Agentic Retrieval for Complex Tasks
Modern information systems, including many agentic workflows, use dense retrieval to explore large amounts of unstructured data.Constraint-Aware Conversational Job Recommendation in Code-Mixed Low-Resource Settings
Conversational job recommendation requires jointly modeling semantic relevance, user preferences, eligibility requirements, and the noisy language used in real-world career discussions.Protocol-Sensitive Evaluation of Log Anomaly Detection: Component Costs and Target-Access Sensitivity on HDFS and BGL
Protocol choices can change the conclusions drawn from log anomaly detection benchmarks even when detector settings are fixed.OntoInk: Interactive Ontology Visualization, Validation, and Reasoning
Ontology documentation, visualization, and validation are usually carried out with separate tools.MATE: Adaptive Long- and Short-Term User Memory for LLM-Based Recommendation
Large language model (LLM)-enhanced recommender systems leverage rich item semantics to support personalized recommendation.Beyond States: Investigating the Effects of Context on User Modeling with Feature-Conditioned Markov Models
User behavior simulation is widely used to evaluate interactive information retrieval systems, but classical state-based approaches (e.g., Markov models) have limited ability to incorporate…Commercial Intent in Human-AI Conversations: A Corpus Audit and Architecture for Website Sales Agents
Conversational sales agents must distinguish questions about products from purchase commitments, preserve explicit requirements, and ground the next action in current business information.Mind the Execution Gap: Action-Semantic Mismatch in World-Model Control
World-model controllers rely on action-conditioned dynamics for prediction and planning, yet real control systems often execute commands asynchronously due to communication delay, packet loss…SPRIG: Semantic-ID-enhanced Paths for Knowledge Graph-based Generative Recommendation
Recommender systems leveraging generative models often generate item identifiers directly, rather than ranking catalog items by a recommendation score.Optimal compression with quantum retrieval
We consider the following data compression problem.Reading the Mood: Emotion-Guided Book-to-Music Recommendation via CGANs and LLMs
Background music that matches the mood of a text has been shown to make readers feel more immersed and improve their reading experience, motivating recommender systems that pair books with…Smart Content Ingestion for Generative AI Workloads
The evolution of machine learning has progressively changed where intelligence resides in an AI system.Beyond Successor Accuracy: State Retention for Recursive Self-Improvement in Recommendation
Recommendation recursive self-improvement (Rec-RSI) feeds recommender outputs into subsequent training.CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets
Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful reading of accompanying dataset documentation.RAGFlip: Measuring Query-Level Negative Flips in Retriever Upgrades
Retriever upgrades are typically evaluated using aggregate metrics, which can hide regressions on queries the previous retriever already served correctly.The Right Memory in the Wrong Context: Verifying Retrieval Admissibility in Long-Term Agent Memory
Long-term-memory agents can retrieve relevant information that is inadmissible for the current request because it belongs to another principal, violates policy, or reflects an incompatible lifecycle…WildMatch: Weakly Supervised Image Matcher Adaptation for Wildlife Re-Identification
Individual animal re-identification from camera-trap imagery is an instance retrieval problem central to non-invasive wildlife monitoring: a query image must retrieve the correct individual from a…