Applied & Human-Centered · Computer Science & AI
Information Retrieval
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979 papers, from 4 September 2026 to 5 November 2026: 979 arXiv preprints.
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Newest papers, page 43
Quanta: A Self-Contained Python Library for Hybrid Retrieval over Quantised Embeddings, Lexical Indexes, and Knowledge Graphs
An advanced retrieval-augmented generation pipeline is typically assembled from three or four independently operated systems: an approximate nearest-neighbour index, a full-text search engine, a…One-Step Retrieval Framework for Real-Time Sponsored Search Ads Using Hierarchical Text Representations
Traditional retrieval systems typically use multi-stage cascading architectures (MCA), where each module is optimized independently, leading to inconsistent objectives and the premature elimination…Understanding AI Provider Recommendations in Local Service Markets
When someone asks an AI assistant which doctor to see or which firm to trust with their savings, the answer is a referral.Exploring LLMs and RAG for Plausible and Explainable Material Prediction of Vehicle Components
In this work, we explore whether LLMs can accurately predict and explain plausible materials for vehicle components such as brake discs or fuel injectors without requiring extensive fine-tuning.SEEK: Secure and Efficient Encrypted Keyword Search For Privacy-Preserving Messaging Protocols
Encrypted communication protects sensitive user data but can facilitate harmful or unlawful exchanges, creating a trade-off between detecting dangerous messages and preserving end-user privacy.SURF: Subtractive Updates for Recommender Forgetting
The increasing demand for user privacy and compliance with regulations such as GDPR has made machine unlearning a fundamental requirement for modern recommender systems.Characterizing Web Search by Conversational LLM Agents: From Search Decisions and Strategies to Results and Responses
Conversational LLM agents increasingly rely on Web search, yet the end-to-end lifecycle of agentic search remains poorly understood.Beyond Private Training: The New Landscape of AI Privacy
Retrieval-augmented systems increasingly rely on vector indexes that may retain deleted items in their search graph.Algebraic Retrieval: Composable Search for Agents
Algebraic Retrieval lets AI agents compose search strategies at query time.SCOUT: Sim-to-Real Text-Based Person Retrieval by Embedding-Space Prediction over Frozen Video Features
Text-based person retrieval under a sim-to-real gap (synthetic training data, a real-image gallery) is usually tackled with costly fine-tuned cross-encoders.PCap: Personalized Retrieval-Stage Diversity Capping in Facebook Marketplace
We propose a personalized capping framework (PCap) to improve the diversity in Facebook Marketplace by introducing user-level diversity constraints at the retrieval stage.Predicting Partial Answer Quality and Utility in Agentic Retrieval-Augmented Generation
Agentic Retrieval-Augmented Generation (RAG) has become a promising paradigm for multi-hop question answering, where a reasoning model iteratively issues queries to a retriever and incorporates…ReliGRec: Reliability-Oriented LLM-Based Generative Recommendation via User-Risk-Aware Prompt Routing
User behavior in real-world recommender systems is heterogeneous.Measuring Decision-Scale Use in Tool-Augmented LLMs: A Contrastive Urban Benchmark
Urban decision-support often asks whether activity is unusually high or low for a specific place, not which place has the larger raw count.AURA: Agentic Diagnosis and Refinement for Production Recommender Systems at Scale
How and why does a recommender system fail the users it serves?Quantifying Organizational Environmental Action from Web Data and Large Language Models
Quantifying organizational environmental action from publicly available web content remains a challenging environmental data science problem because relevant information can be dispersed across…LSREP: A Longitudinal State-Replay Protocol for Evaluating Conversational Memory, with ICE v2 as an Audited Local-First Architecture
Conversational memory changes during use, so endpoint question answering alone cannot establish how a persistent state accumulates, ages, or incorporates revisions.Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?
While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable structures.RegRet: Enhancing Region-Level Retrieval in Large Multimodal Models
Region-level retrieval aims to align user-specified image regions with relevant regions or textual descriptions, playing a crucial role in realworld applications such as e-commerce product search…Efficient Swing Computation for Retrieval in Large-Scale Recommender Systems
Given a user-item graph $G$, a query item $v_q$ and a target item $v_t$, the Swing score $sw(v_q, v_t)$ of the item pair $(v_q, v_t)$ leverages the user-item-user interaction structure to evaluate…