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 13
Theoretically Sound Item Similarity Measures for Recommender Systems
Quantifying the similarity between items is fundamental to neighborhood-based collaborative filtering, yet many commonly used similarity measures are heuristics that lack theoretical justification.Multimodal Requirements Traceability Link Recovery in Industrial Settings
Requirements traceability links support activities such as change-impact analysis, coverage checking, and validation.The Price of Scale in Proactive Memory Recall
A long-lived assistant that brings up memories without being asked must decide at every turn whether anything in its store is worth an interruption.RefinedGAW: A Refined German Academic Web Dataset
The largest open German text datasets are built from broad web crawls, which provide scale but limited coverage of specific domains.HARP-LoRA: Hierarchy-Conditioned Rank Projection for Low-Rank Adaptation in Scientific Table Understanding
Tabular data is widely used in scientific applications, where complex layouts, including multi-level headers, merged cells, captions, and footnotes, make information extraction difficult.DuQUAD: A Dual-View Framework with Quality-Aware Evidence Pruning for Multi-Document Question Answering
Large language models with retrieval-augmented generation systematically underutilize evidence in the middle of multi-document contexts, a phenomenon known as Lost in the Middle.PinGER: Token-Efficient Generative Retrieval with Semantic IDs
Generative retrieval replaces nearest-neighbor search with token-by-token decoding of an item's semantic ID (SID).DyHist: Query-Aware Historical Dynamics Modeling for Temporal Knowledge Graph Extrapolation
Temporal Knowledge Graph (TKG) extrapolation aims to predict future facts from observed historical events.Novel or Not? PatEx-Gym: Agentic Prior-Art Search for Novelty Assessment in Patent Examination
Patent examination is a challenging real-world task that requires agents to discover sparse prior art, iteratively refine queries, inspect technical evidence, and produce novelty assessments…SkillQR: Agentic Skill Discovery for Reason-Intensive Query Rewriting
Dense retrievers provide grounded evidence that mitigates hallucinations in outputs from Large Language Models (LLMs).TriageRAG: Failure-Aware Self-Training for Adapting Retrieval-Augmented Language Models to Specialized Domains
Retrieval-augmented generation (RAG) lets large language models (LLMs) answer knowledge-intensive questions from retrieved evidence, but adapting a general-purpose RAG system to a specialized domain…Bridging Search Intent and Tabular Data in Dataset Search
Dataset search remains a bottleneck in data analysis workflows, as existing systems largely rely on keyword matching or shallow retrieval that fail to capture user intent.After One-Click Video: The Inflow of Service-Type Content, the Failure of the Recommendation Pool Mechanism, and the BoLe System
In September 2026, a new large language model was released.Scaling Graph Query Processing: Focused Exploration on Partitions Using Load Balancing
The focus of this paper is on query processing and not search (approximate or exact).From Item Scores to Semantic Tokens: Test-Time Collaborative Adaptation for Generative Recommendation
Generative recommenders using semantic identifiers predict items through successive token decisions, but beam search may irreversibly prune promising item paths.PersonalQuery-Benchmark:Evaluating Retrieval Robustness to Personalized User Expression Differences
Existing personalized information retrieval methods mainly model differences in user needs through user preferences and query intent, while paying little attention to the personalized expression…System One models Are Not Better Rerankers
System One models, or decision models, answer a question about an input with a calibrated probability instead of generated text.SkillRep: Characterizing and Understanding the Representation Design Space of Agent Skill Retrieval
Retrieving the right skill from a large library is essential for LLM agents, yet requests and skills are written for different purposes and in different words.Hierarchical GTV Estimation: Bridging the Gap between Container-Level Ranking and Item-Level Conversion
Emerging e-commerce platforms, such as live-streaming and Online-to-Offline (O2O) services, inherently operate under a "Container-based" display paradigm.Agentic Memory Management Is the Next Frontier of Information Retrieval
Information retrieval has long been focusing on connecting people with information they need to complete their tasks.