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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Co-adaptive Rule Routing and Constraining for Structured Knowledge Retrieval
Structured knowledge retrieval acquires task-relevant evidence from structured knowledge sources for downstream tasks.RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation
Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-making and personalized safety are of paramount…EVISTA: Unified Multimodal Video Search with Evidence-Aware Temporal Path Optimization
In the era of big data, precise event retrieval from large video collections has become increasingly important and challenging.A Stateful Research Information Infrastructure for Scientific Discovery
Artificial intelligence (AI) is being applied to an expanding range of scientific activities, including literature analysis, hypothesis generation, software development and automated experimentation.LLM-based User-Product Relevance Evaluation for Dynamic Product Advertising
Dynamic Product Advertising (DPA) retrieval systems are a core component of modern e-commerce advertising; however, their evaluation remains challenging.Fine-Tuning Strategy, Not Just Data: A Statistically Rigorous Audit of Gender and Stereotypical Bias in Embedding Models for HR Recommendation Systems
Embedding models underpin modern job-candidate matching: resumes, job descriptions, and queries are encoded as dense vectors, and recommendations come from nearest-neighbor retrieval over that space.Decoupling Knowledge Forgetting and Refusal Learning in MLLM Unlearning
Current evaluations of multimodal unlearning typically focus on whether a model stops outputting target information.The Company a Question Keeps: Auditing Open Jev-Style Models for Retrieval
Jev's documented interface evaluates typed questions independently against shared evidence.Self-improving data synthesis enables scalable adaptation of embedding models
AI agents require specialised retrieval across domains and tasks, but adapting embedding models is constrained by costly manual training-data design.Data Curation and Model Souping: Unlocking Qwen3-0.6B for MS MARCO Passage Ranking
This report studies passage retrieval and re-ranking on the MS MARCO benchmark using lightweight Qwen3-0.6B models.What Drives AI Citations? Content, Retrieval and Model Knowledge in Generative Engine Optimization (GEO)
Generative search engines such as ChatGPT, Gemini and Perplexity now decide which Web pages users see as sources, and a growing industry of generative engine optimization advises publishers on how…Faithful Query Resolution for Conversational Search
Conversational query rewriting makes context-dependent requests explicit for retrieval, but additional context can introduce an information need the user did not express.MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning
Efficient task scheduling in heterogeneous computing systems remains a fundamental challenge in embedded and high-level synthesis flows.PANINI-DR: Controlled Deep Research through Generative Semantic Workspaces
Deep research requires connecting multiple steps of search, reasoning, and computation, with intermediate findings guiding what to investigate next.Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QA
Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-augmented agents give one model both kinds of…Beyond the Final Embedding: Retrieving Memories from Token-Level Evidence
Memory-augmented assistants retrieve evidence from stored conversations and documents to answer queries.PRIME: Pre-Retrieval Index Modeling Enhancement for Structured Document Retrieval-Real
High-precision retrieval over external knowledge bases is essential for LLM agents to operate effectively.NEAR: Neighborhood-Aware Residuals for Memory Retrieval
Memory retrieval aims to identify evidence from stored records to answer a query.Web$hell: A Unified Interface for Agentic Web Access
Large language model (LLM) agents are becoming direct users of the open web.Beyond Temporal Proximity: Explanatory World Models for Credit Assignment in Reinforcement Learning
Generative Recommenders increasingly use Reinforcement Learning (RL) to optimize outcomes that may appear hundreds or thousands of interactions after a decision.