#Information Retrieval
Latest news articles tagged with "Information Retrieval". Follow the timeline of events, related topics, and entities.
Articles (20)
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๐บ๐ธ Enriching Taxonomies Using Large Language Models
[USA]
arXiv:2602.22213v1 Announce Type: cross Abstract: Taxonomies play a vital role in structuring and categorizing information across domains. However, many existing taxonomies suffer from limited covera...
Related: #Artificial Intelligence, #Knowledge Organization -
๐บ๐ธ Retrieval-Augmented Generation Assistant for Anatomical Pathology Laboratories
[USA]
arXiv:2602.22216v1 Announce Type: cross Abstract: Accurate and efficient access to laboratory protocols is essential in Anatomical Pathology (AP), where up to 70% of medical decisions depend on labor...
Related: #Healthcare AI, #Medical Documentation -
๐บ๐ธ Comparative Analysis of Neural Retriever-Reranker Pipelines for Retrieval-Augmented Generation over Knowledge Graphs in E-commerce Applications
[USA]
arXiv:2602.22219v1 Announce Type: cross Abstract: Recent advancements in Large Language Models (LLMs) have transformed Natural Language Processing (NLP), enabling complex information retrieval and ge...
Related: #Artificial Intelligence, #E-commerce Technology -
๐บ๐ธ SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG
[USA]
arXiv:2602.22225v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has strong potential for producing accurate and factual outputs by combining language models (LMs) with evidence...
Related: #Artificial Intelligence, #Machine Learning -
๐บ๐ธ DS SERVE: A Framework for Efficient and Scalable Neural Retrieval
[USA]
arXiv:2602.22224v1 Announce Type: cross Abstract: We present DS-Serve, a framework that transforms large-scale text datasets, comprising half a trillion tokens, into a high-performance neural retriev...
Related: #Artificial Intelligence, #Scalability -
๐บ๐ธ What Makes an Ideal Quote? Recommending "Unexpected yet Rational" Quotations via Novelty
[USA]
arXiv:2602.22220v1 Announce Type: cross Abstract: Quotation recommendation aims to enrich writing by suggesting quotes that complement a given context, yet existing systems mostly optimize surface-le...
Related: #Artificial Intelligence, #Computational Linguistics -
๐บ๐ธ Generative Agents Navigating Digital Libraries
[USA]
arXiv:2602.22529v1 Announce Type: cross Abstract: In the rapidly evolving field of digital libraries, the development of large language models (LLMs) has opened up new possibilities for simulating us...
Related: #Digital Libraries, #Artificial Intelligence, #User Behavior Simulation -
๐บ๐ธ Position-Aware Sequential Attention for Accurate Next Item Recommendations
[USA]
arXiv:2602.21052v1 Announce Type: cross Abstract: Sequential self-attention models usually rely on additive positional embeddings, which inject positional information into item representations at the...
Related: #Artificial Intelligence, #Machine Learning, #Sequential Modeling -
๐บ๐ธ PRECTR-V2:Unified Relevance-CTR Framework with Cross-User Preference Mining, Exposure Bias Correction, and LLM-Distilled Encoder Optimization
[USA]
arXiv:2602.20676v1 Announce Type: cross Abstract: In search systems, effectively coordinating the two core objectives of search relevance matching and click-through rate (CTR) prediction is crucial f...
Related: #Machine Learning Optimization, #User Experience Enhancement -
๐บ๐ธ RMIT-ADM+S at the MMU-RAG NeurIPS 2025 Competition
[USA]
arXiv:2602.20735v1 Announce Type: cross Abstract: This paper presents the award-winning RMIT-ADM+S system for the Text-to-Text track of the NeurIPS~2025 MMU-RAG Competition. We introduce Routing-to...
Related: #Artificial Intelligence, #Efficient Computing -
๐บ๐ธ Diffusion Generative Recommendation with Continuous Tokens
[USA]
arXiv:2504.12007v5 Announce Type: replace-cross Abstract: Recent advances in generative artificial intelligence, particularly large language models (LLMs), have opened new opportunities for enhancing...
Related: #Artificial Intelligence, #Recommender Systems -
๐บ๐ธ Visual Model Checking: Graph-Based Inference of Visual Routines for Image Retrieval
[USA]
arXiv:2602.17386v1 Announce Type: new Abstract: Information retrieval lies at the foundation of the modern digital industry. While natural language search has seen dramatic progress in recent years l...
Related: #Artificial Intelligence, #Formal Verification, #Graph-Based Methods, #Deep Learning -
๐บ๐ธ Retrieval Collapses When AI Pollutes the Web
[USA]
arXiv:2602.16136v1 Announce Type: cross Abstract: The rapid proliferation of AI-generated content on the Web presents a structural risk to information retrieval, as search engines and Retrieval-Augme...
Related: #AIโGenerated Content, #Search Engine Reliability, #Large Language Models, #EcosystemโLevel Failure Modes -
๐บ๐ธ SQuTR: A Robustness Benchmark for Spoken Query to Text Retrieval under Acoustic Noise
[USA]
arXiv:2602.12783v1 Announce Type: cross Abstract: Spoken query retrieval is an important interaction mode in modern information retrieval. However, existing evaluation datasets are often limited to s...
Related: #Technology Evaluation, #Speech Recognition -
๐บ๐ธ WideSeek-R1: Exploring Width Scaling for Broad Information Seeking via Multi-Agent Reinforcement Learning
[USA]
arXiv:2602.04634v2 Announce Type: replace Abstract: Recent advancements in Large Language Models (LLMs) have largely focused on depth scaling, where a single agent solves long-horizon problems with m...
Related: #AI Research, #Multi-Agent Systems -
๐บ๐ธ Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
[USA]
arXiv:2502.07971v2 Announce Type: replace-cross Abstract: Information retrieval is a core component of many intelligent systems as it enables conditioning of outputs on new and large-scale datasets. ...
Related: #Explainable AI, #Computational Efficiency -
๐บ๐ธ GISA: A Benchmark for General Information-Seeking Assistant
[USA]
arXiv:2602.08543v2 Announce Type: replace-cross Abstract: The advancement of large language models (LLMs) has significantly accelerated the development of search agents capable of autonomously gather...
Related: #Artificial Intelligence, #Benchmark Development -
๐บ๐ธ Completing Missing Annotation: Multi-Agent Debate for Accurate and Scalable Relevant Assessment for IR Benchmarks
[USA]
arXiv:2602.06526v1 Announce Type: cross Abstract: Information retrieval (IR) evaluation remains challenging due to incomplete IR benchmark datasets that contain unlabeled relevant chunks. While LLMs ...
Related: #Artificial Intelligence, #Data Science -
๐บ๐ธ Evaluating the impact of word embeddings on similarity scoring in practical information retrieval
[USA]
arXiv:2602.05734v1 Announce Type: cross Abstract: Search behaviour is characterised using synonymy and polysemy as users often want to search information based on meaning. Semantic representation str...
Related: #Artificial Intelligence, #Natural Language Processing -
๐บ๐ธ DeepRead: Document Structure-Aware Reasoning to Enhance Agentic Search
[USA]
arXiv:2602.05014v1 Announce Type: new Abstract: With the rapid progress of tool-using and agentic large language models (LLMs), Retrieval-Augmented Generation (RAG) is evolving from one-shot, passive...
Related: #Artificial Intelligence, #Machine Learning