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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Graded-Relevance Composed Multimodal Retrieval for E-commerce Visual Search at Scale
Visual search on large e-commerce catalogs must serve both "similarity" queries that ask for items resembling an uploaded image and "modifier" queries that comprise an image and text describing a…Auditing Source Exposure in Baidu and Google AI Search
AI-generated overviews are becoming an increasingly prominent layer of search interfaces, yet their behavior in Chinese-language search remains underexplored.What Makes a Good Semantic ID for Generative Recommendation? A Reproducibility Study
Generative recommendation has emerged as an active research direction, where items are commonly represented by semantic IDs (SIDs): discrete codes generated token by token.UK-PRBENCH: A Paragraph-Level Precedent Retrieval Benchmark for United Kingdom Case Law
Prior case retrieval (PCR) aims to identify precedent cases relevant to a given query case.Ascent: An Agentic System over the Model Context Protocol for Real-World Clinical Data Analysis
Answering epidemiological questions from real-world clinical data requires medical coding, schema-aware SQL, and validation of implicit choices about populations, denominators, and time.GroundedGEO: Auditing the Evidence Gap in Generative Search Rankings
Generative search systems rank products and services for consequential decisions, and publishers can cheaply make candidate text look relevant.ReFilter: Bridging Embeddings and LLM Filtering for Similar Mobile App Retrieval
Retrieving similar mobile applications (apps) is essential for researchers, developers, and end-users.From Offline Proxies to Online Decisions: A Layered Engagement Evaluation Framework for Conversational AI
Online A/B experiments are the decision standard for user engagement, but traffic and readout time limit how many conversational-AI changes can be tested.OBLIQ-IR: Training a Dense Retriever for Oblique Queries
Oblique retrieval, as exemplified by OBLIQ-Bench, asks a retriever to find documents whose relevance is determined by a latent attribute (an implicit stance, an analogous reasoning technique, an…Semantic Candidate-Job Matching: A Comparative Evaluation of Dense Embedding Models in Hybrid Retrieval
This paper presents a comparative evaluation of dense embedding models for semantic candidate-job matching in high-volume staffing workflows.From Ranked Documents to Reliable Contexts: An Answer-Oriented Context Construct Framework for AI Search
Traditional Web search follows a human-facing paradigm in which users inspect ranked documents and synthesize information themselves.PSD: Pseudo Self-Distillation of Memory Representation Capabilities for LLM Agents
Memory systems are becoming a core component of LLM agents, but constructing and maintaining memory remains expensive because it relies on repeated calls to large proprietary language models.Beyond Relevance: Structured Semantic Supervision for Product Search with LLM-Augmented Annotations
E-commerce search requires distinguishing products that are merely related to a query from those that directly satisfy the user's shopping intent.MuSeR: Scalable Long-sequence Recommendation with Multi-interest Modeling
Ultra-long user behavior sequences carry rich signals of stable and diverse preferences, yet industrial recommender systems typically truncate histories to a few hundred actions under strict latency…UNIQUE: A Unified Retrieval and Ranking System for Large-Scale Feed Recommendation
Industrial mobile feed systems rely on a retrieval-ranking pipeline to serve large-scale, heterogeneous, and fast-changing content under strict latency constraints.A Redundancy Reduction Approach for Controllable Sequential Recommendations
Sequential recommendation must operate under long-tailed item distributions and popularity-driven concentration, often forcing practitioners to trade short-list accuracy against long-tail exposure.From UNDRR Reports to Event Records: Schema-Constrained LLM Extraction of Georeferenced Disasters
Disaster-risk-reduction archives describe hazard events in prose that databases such as EM-DAT (Delforge et al., 2025) cannot ingest directly.Explainable Recommendations at Scale: LLM Rationales for YouTube Music Artist Discovery
Modern music streaming platforms face a persistent tradeoff: exploiting familiar content versus driving the exploration of novel items.Q-TIE: A Lightweight and Generalizable Re-ranking Framework for Temporal Information Retrieval
Temporal Information Retrieval (TIR) has been increasingly critical given the rise of Retrieval-Augmented Generation (RAG).Scoring With the Engine: Retrieval Exposure, Cross-Engine Divergence, and the Limits of Engine-Agnostic GEO Scores
Recent work asks whether generative-engine visibility can be approximated with deterministic, engine-free page scores.