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 31
ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research
What makes great scientists great?SOLO: Certified-Recall Metric Similarity Search with Scan-Only Sampled Inverted Lists
We present SOLO, an index for approximate nearest-neighbor search in general metric spaces whose serving path contains no ranking heuristic of any kind: a query is routed to the $k_s$ nearest points…On-Premises Multi-Course RAG Tutoring for Business Education: Hardware-Software Trade-offs in a Campus AI Tutor
Campus AI tutors based on retrieval-augmented generation (RAG) must ground answers in assigned course materials while keeping textbooks and student dialogue on institutional infrastructure.Adaptive Sparsity Optimization with Learnable Soft Top-K and Per-Term Thresholding for Efficient Retrieval
Recent work on neural sparse retrieval has demonstrated strong relevance by leveraging Large Language Models (LLMs) for semantic term expansion.When History Misleads: Asymmetric Margin Supervision for Instruction-Guided LLM Generative Recommendation
In instruction-guided generative recommendation, LLM-based recommenders need to balance two goals: responding to the user's current request and aligning with the preferences in their interaction…Fine-Grained Emotion Classification from Mobile App Reviews: An Empirical Study with Large Language Models
Fine-grained emotion classification of mobile app reviews enables requirements engineering activities that go beyond polarity-based opinion mining, including emotionally informed issue…Learning to Route in Visual Space via Multi-Step Embedding Retrieval
LLM agents rely on retrieval tools to access external knowledge, yet visual agentic search remains severely bottlenecked by standard single-step retrievers.PatchHolmes: Agentic Patch Retrieval via Listwise Selection
Patch retrieval, the task of finding the commit that fixes a known vulnerability, is the foundation of vulnerability management workflows, yet 60% to 63% of CVEs in the major advisory databases lack…SkillSeek: Revisiting Agent Skill Retrieval at Marketplace Scale
Anthropic's Agent Skills package reusable procedural know-how for an LLM agent into SKILL.md directories, and open-source aggregations have grown past 230,000 skills, making selection rather than…TRACE: Target-Aware Retrieval, Attributed Evidence, and Contract-Constrained Extraction for LitTraceQA
Finding a relevant paper is not the same as producing a verifiable answer from it.Breaking News Out of the Filter Bubble: Generative AI Search Diversifies Collective Attention and Raises Shared Information Consumption
Generative AI search and AI overviews are transforming access to information and news, renewing concerns that readers will encounter a narrower range of topics and have less in common.Text-Video Retrieval via Multi-Dimensional Saliency Assessment and Granularity-Aware Query Decomposition
Text-video retrieval, which aims to bridge visual and textual modalities by learning a joint embedding space, has become a crucial task in multimodal intelligence.When LLM-Inferred User Context Adds Value in Production Streaming Recommendation
Contextual information in recommender systems is shifting from static, predefined variables toward latent representations inferred from behavior.RouteRec: Behavior-Guided Sparse Routing for Sequential Recommendation
Sessionized interaction histories contain behavioral patterns that can improve sequential recommendation.Evidence First, Arithmetic Second: A System Report and Failure Analysis for DocSem
EVICALC, our system for the DocSem shared task, achieved 8.61% joint accuracy on 1,730 tasks in the official final test evaluation.Routing Between Generative and Collaborative User Profiles: A Serving-Time Gate for Controllable Novelty
Large language models (LLMs) enable rich semantic user profiles for recommendation, but such profiles are more expensive to generate and are not necessarily desirable to deploy uniformly.O-Funnel: Lossless Structural Capture and Requirement-Driven Extraction from Drifting, Heterogeneous Documents
Pulling a fixed set of fields out of documents that arrive in many formats and under drifting schemas is usually done with hand-written byte patterns, which break whenever a key is renamed, a value…Argument Structure Prediction in Online Conversations: A Comparative Study of Modeling Paradigms and Task Architectures
Argument structure prediction (ASP) constructs complete argument structures from discourse by identifying argumentative units and their relations.Learning Multiresolution Relevance for Hierarchical Generative Retrieval
Generative retrieval with semantic identifiers (SIDs) makes successive decisions over a document hierarchy.Residual Trajectory Distillation for Generative Retrieval
Generative retrieval has emerged as a general retrieval paradigm, representing items with discrete Semantic IDs (SIDs) and retrieving them through autoregressive identifier generation.