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 4
RecRSI: Mechanism-Guided Discovery of Recommendation Algorithms
Improving recommendation algorithms for the Web requires coordinating interacting design choices and learning from experiments.SearchInject: Retrieval Exposure Control for Indirect Prompt Injection in Language-Model Search
An indirect prompt injection can affect a search-augmented large language model only after its carrier page reaches model context.Learning to Adjudicate: Verifier-Guided Multi-Agent Reasoning for E-Commerce Relevance
Relevance modeling is fundamental to e-commerce search, determining how well retrieved products satisfy the needs expressed in a user's query.Bridging Low-Level Image Fusion and High-Level Semantic Understanding
Remote sensing image fusion and semantic interpretation are usually optimized separately, so reconstruction quality need not preserve downstream retrieval utility.PlagiaCorpus: A Bilingual, Adversarial, and Cross-Lingual Dataset for Forensic Plagiarism Detection
PlagiaCorpus is a bilingual Arabic-English dataset for benchmarking plagiarism and text-reuse detection, including reuse produced by large language models (LLMs) and reuse across languages.E-GenRM: Generative Reward Modeling for Open-Ended E-Commerce Shopping Agents
We present E-GenRM (E-commerce Generative Reward Model), a generative reward model tailored to e-commerce shopping agents.PACERec: Progressive Adaptation of LLM Item Embeddings with Collaborative Evidence for Recommendation
Large language model (LLM) embeddings have been increasingly adopted in sequential recommendation to encode static item attributes and alleviate the limitations of item ID embeddings under sparse…DR Pixel: Page-Native Deep Research with Vision-Language Models
Complex documents such as scientific papers contain rich information in tables, figures, and equations; however, existing deep research (DR) agents typically reduce papers to OCR-extracted text.Preprocessing Choices in Fine-Tuning Data Matter: Utility and Demographic Sensitivity in LLM-Based Recommendation
Large language models (LLMs) have introduced a generative approach to recommendation, producing item lists from textual representations of user histories and item information.Every Clause Counts: Instruction-Following Reranking by Multiplying Small, Answerable Questions
People often attach instructions to their search queries, asking for pages written for beginners, documents in a certain language or official sources only.Dhārā Bench: An Evidence-Oriented Retrieval Benchmark for Indian Knowledge Systems
Dhārā Bench is a retrieval benchmark for Indian Knowledge Systems (IKS), with 325 questions in 12 categories and 60,121 text chunks from 15 source groups.Diverse-Teacher On-Policy Distillation for Generative Recommendation
Generative recommendation generates the semantic ID (SID) of the next item from a user's interaction history.From FAIR to AI-FAIR Metadata-First Infrastructure for AI-Enabled Science
Artificial intelligence (AI) technologies and their capabilities have advanced rapidly over the past few years, leading to widespread interest and adoption in the biological and ecological sciences.EvoMemState: Evolving Memory State for Personal Agents
Long-term memory enables large language model (LLM) agents to provide continuous personalized assistance by retaining user information across interactions.Enhancing Stock Market Information Retrieval with Retrieval-Augmented Generation
Natural Language Processing (NLP) has been widely applied in financial domains, enabling automated analysis and retrieval of stock market information.Rethinking Next-Visit Diagnosis Prediction Beyond Aggregate Metrics: Retrieval--Memory Multi-Agent Adjudication
Next-visit diagnosis prediction forecasts the diagnoses documented at a patient's next encounter, turning retrospective electronic health records into prospective clinical prediction.Modular and Efficient Approximate Nearest Neighbors Search with Vectorium and kANNolo
Approximate Nearest Neighbors (ANN) search over neural embeddings powers modern retrieval systems such as Retrieval-Augmented Generation.Characterizing Adversarial GEO via Implicit Brand Injection
Generative search engines increasingly shape how users discover products, services, and commercial entities by generating answers from retrieved web content."PRISM" Is Not All You Need: Cross-Topic Name Collisions and Scientific Paper Retrieval
Scientific names increasingly connect papers from different research topics, leaving readers to recover a paper's identity from context.CCD: Context-Calibrated Open-Entity Out-of-Distribution Detection in In-Context Tabular Foundation Models
In-context tabular foundation models (TFMs), such as TabPFN, predict from a labelled context without updating their parameters and are increasingly used for out-of-distribution (OOD) detection in…