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 15
The Delayed Countdown Method for Validating Review-Oriented AI Workflows in eDiscovery
Review-oriented workflows have become the dominant approach to AI-assisted document review in electronic discovery (eDiscovery).SurveyGraph: Generating Academic Surveys via Methods-Entity Knowledge Graphs
Most automated survey generation systems retrieve papers as flat documents, limiting their ability to capture research structure.A Task-Centric Survey of Long-Document Visual Question Answering: Taxonomy, Evolution, and Future Directions
Visual document understanding is essential for acquiring knowledge from visually rich documents and is attracting growing research interest.What the Query Remembers: Query Abstraction Governs Lexical and Dense Retrieval of Classical Arabic Poetry
How well a poetry archive can be searched depends on what the user still remembers, not only on what the model understands.Machine-Readable Operator Manuals over the ISO 11783 Network for Offline, Multilingual LLM Assistance
If agricultural machinery is to support intelligent, offline assistance, then the system must access technical documentation dynamically.Mining Frames: Association Rule Mining as an Unsupervised Framework for News Framing Detection
Computational framing analysis is dominated by supervised classifiers that require large annotated corpora and predefined frame taxonomies, limiting their use for non-English languages, novel…MICE to Meet You: From Re-ranking Only to End-to-End Retrieval
Late-interaction models offer state-of-the-art efficiency-effectiveness trade-offs for neural retrieval by enabling document representations to be pre-computed and efficiently indexed.A Model-Agnostic Correction Framework for Short-Term Building Load Forecasting
Short-term building load forecasting remains challenging because load patterns can change rapidly with weather and operating conditions.Our Own Jev: Typed Decisions in One Forward Pass, from an In-House Judge to Open LoRA Models
A typed decision maps evidence, a question and a fixed set of options to a probability for every option, computed in one forward pass, by reading a language model's logits or a small head over its…Progressive Learning from Content to Relevance to Personalization for CTR Prediction
Multimodal click-through rate (CTR) prediction is central to search systems, where ranking depends on item content, query relevance, and user preference.Reasoning-Search-Augmented LLMs: An Operational Taxonomy, Benchmark Analysis and Controlled Evidence Synthesis
Large language models (LLMs) demonstrate impressive emergent reasoning capabilities, yet they remain constrained by fixed model parameters and finite context windows.Preference Is Not Permission: Personalizing the Auto-Purchase Line in Agentic Commerce
Personalized shopping benchmarks ask which item fits the user; we ask how far an agent may commit on that item, and pose learning the individual's auto-purchase line as a task.Learning Marginal Viewpoint Utility for Budgeted Evidence Selection in RAG
Retrieval-augmented generation over multi-viewpoint queries must preserve distinct answers and positions from the retrieved evidence while operating under a fixed context budget.Extending FAIR Principles with Observability for Trustworthy Federated Learning
Federated learning (FL) keeps data at its source, but locality alone does not make a federation trustworthy.Generative Recommenders Forget the Long Tail: Restoring Memorization in Retrieval and Ranking
Generative recommenders replace the retrieve-then-rank cascade with a single model: beam search over semantic item identifiers performs retrieval, and the same likelihood performs ranking.Directional Posterior Feedback Fusion for Query Reformulation in Dense Retrieval
Dense retrieval has become a fundamental paradigm for modern information retrieval, supporting efficient semantic search across a wide range of applications.Beyond the Vote: When Do LLMs Add Value to Retrieval-Based Tabular Classification?
Retrieval-based in-context learning (ICL) enables large language models (LLMs) to predict tabular labels from similar examples, but it remains unclear whether LLM inference improves on direct voting…X-Embedding: Two-Stage Training for Multilingual Patent Prior-Art Retrieval
Multilingual patent prior-art retrieval requires identifying X-category references that are particularly relevant to the novelty or inventive step of a claimed invention, beyond topical similarity…pplx-embed-v2-late Technical Report
In this report, we introduce pplx-embed-v2-late, a pair of 0.6B and 9B multilingual and multimodal late-interaction models.SOAR: Social and Opinion-Aware Recommendations
One of the enduring challenges in online platforms is recommendation.