Applied & Human-Centered · Computer Science & AI
Information Retrieval
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979 papers, from 4 September 2026 to 5 November 2026: 979 arXiv preprints.
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Newest papers, page 47
Generative Late-Interaction Embeddings For Visual Document Retrieval
Late-interaction retrieval is the state-of-the-art for visual document search, but it pays for its accuracy in storage.Extracting Dataset Mentions in Forced Displacement and FCV Documents: A Weakly Supervised Framework with LLM-Based Label Refinement
Development and humanitarian organizations produce and support surveys, administrative registries, and other data resources to inform research, policy, and operations, yet systematically identifying…EAR: Entity-Aware Partitioning Approach for Retrieval-Augmented Generation Development
Retrieval-augmented generation (RAG) can improve knowledge-intensive question answering, but the first design choice is easy to overlook: how should the source corpus be partitioned into retrievable…Recommendation Retrievers Need Verifiers: Universal Generative Reranking for Sequential Recommendations
First-stage recommenders in multi-stage systems produce a ranked candidate list from which a limited prefix is forwarded to downstream rankers.Decoupling Error Attribution in Cloud-Native Graph-RAG: A Data Integrity Diagnostic Framework
Graph-RAG systems often assume pristine data quality, overlooking the severe impact of perturbations in cloud-native databases.High-probability guarantees for linear accessibility in feature superposition
Neural networks can leverage feature superposition to encode more concepts than dimensions, but cross-feature interference constrains the linear accessibility of simultaneously active features.Should I Be Polite to My LLM Relevance Judge? Tone as a Severity Operating-Point Shift
Large language models are increasingly used as relevance judges, yet their labels can shift with prompt surface form.When Does Low-Bit Quantization Preserve the Decisions of Vector Search?
Low-bit quantization can achieve high recall on some vector representations and fail sharply on others, while average distortion and global rank correlation do not explain the difference.Purchase Advice and Observable Buyer Responses in Real AI Conversations
How often does a generative assistant persuade someone to buy, or persuade them not to buy?Guaranteeing Faithful Evidence Extraction in Speculative Retrieval-Augmented Generation
Large Language Models (LLMs) are increasingly used as interfaces for information retrieval, but they remain prone to hallucinations and faithfulness errors, in which the generated answers diverge…From Retrieval to Weights: Parametric Individualization of Small Language Models with Individual Text Corpora
We approach a cognitive simulation perspective on episodic and semantic memory in multiple-choice question answering by incorporating text from individual text corpora (ITC) into retrieval-augmented…The Answer Path and the Grounding Instruction in LLM Question Answering over Knowledge Graphs
A graph retrieval-augmented generation pipeline chooses which triples to put in the prompt, a syntax to write them in, an order to write them in, and a sentence telling the model what to do with them.LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation
Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversized contexts that reduce generation efficiency.GANDR: Claim Auditing for Verifiable Legal Answer Generation
In high-stakes domains such as legal practice, a language-model answer is only useful to the extent that a reader can verify each claim against the source the system cites.Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs
Enterprise data lakes accumulate tables faster than human stewards can document or classify them, leaving columns with missing descriptions and unassigned governance labels.When Synthetic Data Hurts: On Catastrophic Forgetting in Skill Retrieval for LLM Agents
LLM agents increasingly rely on external skills retrieved at runtime, making skill selection from large repositories a critical challenge.Following the Preference, Missing the Optimum: Compliance Without Optimization in AI Housing Recommendation
Large language models are becoming the first point of contact for consumer search in domains where the stakes are material and the law is explicit.Project Qualia: Recovering Experiential Music Structure from Session Co-occurrence Data
This report presents results from Project Qualia, an ongoing effort to determine whether experiential similarity between songs, a structure not captured by genre or metadata taxonomies, can be…Artificial Intelligence-Assisted Digital Inventory of Cultural Heritage & Traditional Knowledge: Case for Indonesian Open Digital Library of Culture
The Indonesian Digital Library of Culture (Perpustakaan Digital Budaya Indonesia, PDBI; budaya-indonesia.org) is a participatory platform that has collected tens of thousands of entries on Nusantara…Snugi-AI-v2 @ eRisk 2026 Task 2: Early Depression Detection via a Learned Stopping Policy with Sustained Confidence Gate
We describe the Snugi-AI-v2 submission to eRisk 2026 Task 2, the second edition of contextualized early depression detection from Reddit discussions.