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 8
From Intent to Improvement: Agentic Dataset Search for Better Model Training
Finding training data in million-scale machine learning repositories is a Web search problem where text relevance is not enough.GistRank: Gist-Compressed Listwise Ranking with Large Language Models
Large language models (LLMs) have become a powerful tool for listwise relevance ranking, which can improve web search by comparing retrieved passages jointly.Efficient LLM-based Subgraph Retrieval for Multi-Hop Knowledge Base Question Answering
Multi-hop Knowledge Base Question Answering (KBQA) aims to find answer entities in the knowledge base that are multiple hops away from the entities in the question.Heterogeneous Co-Evolution Learning for Tool-Efficient Search Agents with Zero Labels
Deep search agents extend language models by interleaving reasoning with external retrieval.R2QRec: Learning Recommendation Queries from Retrieval Feedback
Query-based recommendation separates expressing user needs from locating matching items.Beyond IPS: Reliable Counterfactual Evaluation in Multi-Stage Ad Systems without Logged Propensities
Offline evaluation of ad-ranking policies in multi-stage delivery systems is challenging because action propensities are often unavailable, limiting inverse propensity scoring (IPS).xPRT: Cross-Passage Retrieval Pretraining
Dense retrievers are a foundational component underlying modern RAG and search systems.Towards Full-Text Scholarly Argument Mining using Entity-Anchored Claim Extraction
Argument mining in full-text scholarly articles remains an important yet challenging task.Decompose, Estimate, Select: Coverage-Aware Context Construction for Long-Form RAG
Retrieval-augmented generation (RAG) grounds a language model's output in retrieved evidence, but for complex questions spanning multiple aspects of an information need, relevance-based retrieval…Glance: The Generator Is Its Own Reranker
Retrieval-augmented generation commonly serves separate models for reranking and answering, duplicating model residency and passage processing.Testimony from Timelines: Evidence-Grounded Significance Testing of Temporal Clinical Hypotheses
Ask a language model whether sales tend to dip after a product recall, or whether one side effect tends to follow another after a vaccine, and it answers in a fluent sentence that reads like a…Prevented is Not Protected: What Attack Success Rate Hides about RAG
Retrieval-Augmented Generation (RAG) is vulnerable to knowledge poisoning, where adversaries manipulate retrieved evidence to influence model outputs.Retrieve-then-Disambiguate: Scalable Reviewer Discovery
The growing number of scientific submissions is straining the peer review process, while a large pool of relevant researchers remains unidentified and is therefore not considered as potential…ProdCrawl: A Replayable Test Collection for Focused Crawling
A focused crawler searches for web pages on a specific topic under a constrained download budget.FieldGuideRAG: Image-Grounded GraphRAG for Fine-Grained Recognition with Vision-Language Models
We present FieldGuideRAG, a training-free GraphRAG method in which a vision-language model, or VLM, recognizes fine-grained species by comparing the query with real photographs stored on the nodes…WebOverlay: High-Throughput Vision-Only Distillation for Extreme Aspect-Ratio Web Overlay Detection
Web overlays, such as cookie consent banners, newsletter prompts, and age gates, obstruct automated web crawlers and degrade downstream document representations.Predicting What Answer Engines Cite: Open Decision Models, Rerankers and a Distilled 4B Student on Ten Engines under Controlled Retrieval
Generative engine optimization needs a scorer that ranks candidate pages by the share of an answer they will receive as citations.Manifest-Assisted Retrieval in Artificial Intelligence Search: Evidence Gaps and a Security Evaluation
The external sources retained in our non-systematic audit did not isolate the incremental security or utility effect of consuming /llms.txt while ordinary retrieval remained fixed.Towards Reliable, Scalable, and Value-Aligned Generative Recommendation for Large-Scale Advertising
Generative recommendation (GR) reformulates item retrieval as autoregressive generation of discrete semantic identifiers (SIDs), offering a unified paradigm for personalized recommendation.CoWalk: Cooperative Walks for Agentic Batch Queries on Disk-Resident Graphs
Workloads such as query rewriting, deep research and group-relative policy optimization (GRPO) issue batches of semantically related vector queries.