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 48
Cassette: Case-to-Case Structural Distillation for Efficient Legal Case Retrieval
Legal case retrieval (LCR) is an essential tool for not only assisting legal practitioners to efficiently retrieve precedents but also enabling ordinary individuals to find valuable legal case…Bridging the Semantic-Utility Gap in Multimodal RAG via Generator-in-the-Loop Alignment
Vision-language models (VLMs) augmented with retrieval-augmented generation (RAG) benefit from access to external evidence.Evidence-Aligned Entity Verification for Hallucination Detection in Retrieval-Augmented Generation
Hallucination detection is crucial for large language models (LLMs), as hallucinated content creates significant barriers in applications requiring factual accuracy.Exploring Bottom-Up Clustering for Creating Semantic IDs
The success of generative retrieval has largely been attributed to the use of Semantic IDs, which improve over arbitrary item-level identifiers such as hashes by capturing the semantics of items.Tool Retrievers Are Underestimated: Annotation Expansion Reveals True Capability
In open-world scenarios with massive and evolving tool repositories, tool-augmented large language models rely on a retriever to surface relevant tools for a given query.SequenceO1: End-to-End Ultra-Long (100K) Sequence Modeling in Recommendation with Low-Rank Caching
Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking models operate under strict latency, memory…Individual Text Corpora Predict User-Specific Knowledge: Benchmarks of Individualized Knowledge Simulation
This study examines whether individual text corpora (ICs) from search histories can be used to simulate individual knowledge.PDMR: Passage-Driven Multi-ID Document Retrieval
Generative Retrieval (GR) models map queries directly to document identifiers, replacing conventional retrieval over external sparse or dense indexes with autoregressive identifier generation.REDSI: Addressing the Reproducibility and Evaluation Consistency of Differentiable Search Indexing for Document Retrieval
The differentiable search index (DSI) framework (Tay et al., 2022) has become the de facto baseline for generative retrieval.Q2D-Web: A Large-Scale Benchmark for Retrieval in Agentic RAG Systems
Evaluating first-stage retrievers in large-scale production RAG requires a benchmark that pairs a large-scale corpus with a large set of agent-reformulated search queries based on real user queries…FINALLY: A Dataset Recommender System for Recommender-Systems Research
Dataset selection shapes the empirical conditions under which recommender-system algorithms are evaluated, yet existing tools provide limited support for constructing complete dataset sets that…Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation
Automatic fact-checking systems assess the veracity of claims given evidence from relevant documents.Extracting Semantics from Cattle Reporting Categories for Data Interoperability and Findability
Livestock population data disaggregated by age, sex, and production are important inputs to calculations and models that inform our understanding of global health, yet these data are fragmented…Beyond One-Shot Expansion: Contrastive Evidence Exploration for Multi-Hop Retrieval
Retrieval-augmented generation (RAG) critically depends on retrieving the evidence necessary for effective reasoning.Where to Look and What to Use: Retrieve-Localize-Generate for Long-Term Conversational Memory Question Answering
Retrieval-augmented generation (RAG) enables large language models (LLMs) to answer questions by accessing external knowledge and has been widely adopted for long-term conversational memory question…Query-Aware Token Budgeting for Efficient Late-Interaction Visual Document Retrieval
Late-interaction visual document retrievers preserve fine-grained page evidence by storing many token embeddings per page, but the resulting storage and query-time interaction costs make large-scale…Matryoshka Hash Representations for Model-Aware Compact Semantic Retrieval
Retrieval-augmented generation (RAG) depends on dense retrieval: each document is stored as a learned vector, and a query is answered by finding its nearest neighbors in that vector space.EigenLI: Spectral Approximations to Late Interaction
Late-interaction models such as ColBERT achieve strong effectiveness by representing each document with many token-level vectors, but this expressivity leads to large indexing cost, storage…Same Problem, Different Field: Cross-Domain Solution Import via Domain-Stripped Computational Fingerprints
The same underlying computational problem is solved across unrelated fields under different names: recursive Bayesian state estimation appears as a "Kalman filter" in control, "Bayesian forecasting"…Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?
Democratizing access to the knowledge held in large corpora of tables such as data lakes is emerging as a central research challenge.