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 41
DOA-SORT: Directional Occlusion-Aware Multi-Object Tracking with Distributional Observations
Identity association in multi-object tracking (MOT) is vulnerable to partial occlusion, truncated detections, and fluctuating confidence scores.Beyond Raw Engagement: A Counterfactual Observability Framework for Recommender Systems at Netflix
Understanding the performance of large-scale recommender systems remains an underexplored challenge, especially for content creators and model developers.Parameterized Dense-Sparse Fusion for Hybrid Retrieval: Tuning a Rank-Score Mix on BEIR SciFact with Qdrant
We study a parameterized hybrid ranker that fuses a dense embedding list and a sparse lexical list.Per-Query Gating of LLM Rerankers for Multi-Hop Retrieval
LLM rerankers add of the order of \$0.2-0.3 per 1,000 queries and about a second of tail latency on top of a graph-augmented dense pipeline such as HippoRAG2, and on three multi-hop benchmarks they…R-GEAN: Regimen-Guided Edit Action Network for Within-Admission Medication Change Prediction
The medications prescribed to a patient often change during a hospital admission as clinicians start, stop, or continue therapies.Attributable Post-Rationalization in RAG Citations: A Controlled Reproduction and an RLVR Comparison
A RAG system can hand you the right answer and cite a source it did not actually use.Bridging Static and Agentic RAG for Taiwanese Historical Question Answering
Agentic retrieval-augmented generation (RAG) enables language models to adapt retrieval based on previously retrieved evidence, but it remains unclear whether such adaptive orchestration…Inherit4Rec: Parameter Inheritance for Efficient Scaling of Recommendation Models
Scaling model capacity has emerged as an effective approach to overcoming performance bottlenecks in industrial recommender systems.Improving disruptive research in the EU: why strengthening European Research Council grants alone is not enough
Disruptive innovation in the EU is not sufficiently competitive; this weakness puts at risk the social benefits that its citizens take for granted.MM-ContextFold: Context Folding for Multimodal Agentic Retrieval
Multimodal Agentic Retrieval (MAR) requires agents to solve complex information-seeking tasks by iteratively invoking external tools.From Prompt to Recommendation: A Fitted Stage Model of Brand Visibility in AI Search
We analyze 34,960 unbranded prompt-engine observations from 75 anonymized Aiso projects, covering 2,854 distinct monitored prompts and repeated GPT and Gemini runs from June-September 2026.Verify, Don't Trust: Agentic Model Development for Video Discovery Retrieval at Scale
Large language model (LLM) agents can propose, implement, and evaluate model changes.Hybrid GPU-CPU Retrieval for Personalized Search at Ultra-Large Scale
Embedding-based retrieval on user-generated content at the trillion-document scale exposes a sharp conflict between two production demands: deep, expressive personalization for queries with rich…Auto-Bidding with Disentangled Advertiser Profiles and Train-Free Adaptation
Auto-bidding is a key component of modern advertising systems that provides a personalized bidding strategy for each advertiser.Adaptive Preference Modeling via Explicit Indirect Relational Learning for Personalized Fashion Matching
Personalized fashion complementary recommendation requires jointly modeling user preferences and item compatibility under sparse and multimodal data conditions.Do We Care About Personalization and Explainability? An Interview Study with News Recommendation Engineers
Research on explainability in recommender systems largely centers on end users, overlooking the perspectives of those who build and maintain these systems and their potential use cases such as model…AutoRecLab: Describe the Experiment, Get the Code!
Empirical evaluation is central to recommender-systems (RecSys) research, but turning experimental designs into executable code remains a manual and error-prone task.Predictable Failure in Multi-Hop Retrieval: Score-Distributional Confidence Scoring and Abstention
Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations.Semantics Delivery Network: Rethinking Web Retrieval Infrastructure for LLM Agents
Large language models (LLMs) increasingly rely on external sources when answering questions that require proprietary information or up-to-date live web content, through both traditional single-shot…IntLawNER: A Named Entity Recognition Dataset and Benchmark in International Law
International law provides the normative framework through which states coordinate action, regulate armed conflict, and protect human rights, yet its texts remain without token-level named entity…