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 35
ThuRunel: Dynamic Decoupling for Structured Advisory Dialogue
High-stakes advisory domains such as medical aesthetics, legal consultation, and educational planning exhibit a two-phase structure.Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning
Graph-based approximate nearest neighbor search (ANNS) is widely used for large-scale semantic search.ARCagent: An Adaptive Retrieval Calibration Agent for Clinical Question Answering
In diseases where clinical guidelines are incomplete, contested, or mutually contradictory, knowledge completeness and dynamic conflict-aware synthesis are two safety-critical properties that…Overview and Analysis of the RecSys Challenge 2026: Conversational Music Recommendation
The RecSys Challenge 2026 studies conversational music recommendation as a joint item recommendation and response generation problem: given a multi-turn dialogue, systems must retrieve relevant…Algorithmic Harms Associated with Generative Model-Augmented Recommendation Systems
In this work, we consider algorithmic harms that may arise as generative models are incorporated into machine learning platforms.Inspire: Benchmarking Scientific Literature Search for Open Research Problems
Scientific literature search often begins with an open research problem rather than a known target paper or a fixed candidate set.Robust Hierarchical Structures for Agentic Document Analysis
Large Language Models (LLMs) enable us to better understand text documents, including PDFs and Word documents.What Gets Measured Gets Managed: Sign-aware Recommendation Needs Sign-aware Evaluation
Sign-aware recommender systems have recently been developed to leverage negative feedback for a deeper understanding of user preferences.From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelines
Guideline documents are published as unstructured PDFs whose evidence is locked in visual structures---tables, flowcharts, and graded recommendations---that standard retrieval pipelines flatten into…Learning Multimodal Embeddings with Evidence-Aligned Readout
Multimodal large language models can expose task-relevant evidence through generation, but producing useful evidence does not by itself determine how it enters a retrieval embedding.Beyond the Beam: Constructive Repair and Candidate Completion for Generative Recommendation
Generative recommenders retrieve items by generating identifiers, but a valid identifier can remain outside the beam after catalog expansion.Concurrent Coded Signal-Multiplexing Ranging for Half-Duplex Asynchronous Networks
Signal-multiplexing network ranging (SM-NR) shares broadcasts across node pairs, but its sequential operation leads to a ranging cycle that grows linearly with network size.Beyond Fixed Features: Architecture-Dependent Sensitivity to Node Representations under Heterophily
Graph Neural Networks (GNNs) perform well on homophilic graphs but struggle in heterophilic settings, where connected nodes often carry dissimilar labels.High-Level Text Preprocessing for Semantic Similarity Analysis of Discursive Texts: A Framework and Empirical Demonstration
Semantic Textual Similarity (STS) methods assume that a document's lexical content faithfully represents what it asserts.Relevance Is Not Sufficient Evidence: Detecting Evidence Gaps Before Generation in RAG
Retrieval-augmented generation (RAG) grounds large language models in external sources, but retrieved passages often name the right entities without providing the facts needed to answer.Rethinking Cross-Channel Importance in Time-Series Forecasting
Cross-channel modeling is central to multivariate time-series forecasting, yet channels that are statistically related, predictively useful, and actually used by a trained forecaster are often…DP-Rec: Towards Dynamic Patching for Efficient Long-Sequence Recommendation
Transformers have redefined sequential recommendation by effectively modeling dynamic user behaviors and long-range dependencies.Graph Memory: Spectral Associative Memory via Dirichlet Energy
Dense associative memories have traditionally focused on storing and retrieving vector-valued patterns.When Does Dense Retrieval Need Asymmetric Geometry? A Bias-Variance Theory of Shared and Dual Projections
Dense retrieval powers retrieval-augmented generation, semantic search, and question answering, yet the theoretical basis for choosing between shared and dual query-document projections remains…Beyond Dyadic Memory: Interaction-Aware Multimodal Memory with Adaptive Agentic Retrieval for Multi-Party Spoken Conversations
Long-term memory enables agents to accumulate information and reason across sessions, yet existing research primarily focuses on dyadic text or image-text conversations, leaving long-term memory for…