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.
Get the few papers worth your time in Information Retrieval every morning.
Follow Information Retrieval and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 42
AdaMerge: Tuning-Free Patch Compression for Multi-Vector Visual Document Retrieval
Multi-vector visual document retrieval (VDR) models such as ColPali and ColNomic achieve strong accuracy by representing each document with hundreds to thousands of patch-level embeddings, at…CliniCIRCA: A Modular LLM Framework for Constructing Longitudinal Mental Health Patient Journeys from Raw EHR Narratives
In mental health care, reasoning over patient journeys is a key task for clinicians.FootprintRAG: Visual Analytics for Evidence Context Refinement in RAG-based Scientific Literature Exploration
Retrieval-Augmented Generation (RAG) is increasingly used to ground large language model (LLM) outputs in scientific literature.Semantic Layer Induction from Raw Telemetry via Hierarchical LLM and RAG Abstraction
Modern applications generate massive volumes of raw telemetry data, but translating those noisy, heterogeneous event streams into actionable business insights remains a fundamental challenge.Beyond Similarity through Zero-Token Geometric Graphs for Multi-Hop RAG
Multi-hop retrieval-augmented generation (RAG) requires evidence that remains relevant to a query while introducing enough novelty to bridge semantic gaps.Self-Evolving Search Index
Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs.FINSKILLOPS: A Self-Evolving Multi-Agent System for SEC Filing QA
Financial QA systems are typically improved before deployment through better retrieval, prompting, or agent coordination, leaving their reliability behavior fixed thereafter.Dense Feature Representation over Sequence Modeling: A Solution to the KDD Cup 2026 UniRec Challenge
We describe our 10th-place solution to the KDD Cup 2026 Tencent UniRec Challenge, industrial click-to-conversion (CVR) prediction over 34.82M records, and we ask which mechanisms actually move…Reproducing Transparent and Scrutable Recommendations: Exploring Open-Weight Models via Natural-Language User Profiles
In this reproducibility study, we investigate the transparency and scrutability of recommender systems enhanced by incorporating generated natural-language user profiles that represent user…Trust, but Validate the Instrument: Auditing AI-Generated RTL Verification Plans on Authored Security-Regression Proxies
AI-generated RTL verification plans can satisfy a provider schema yet fail at the boundary to trusted execution.Intrinsic Sequence-Likelihood Confidence in Retrieval-Dominated Extractive QA: Two Pre-Specified Negatives, and What They Do and Do Not Attribute
In extractive document question answering whose questions were generated from the passages that contain their answers -- so that retrieval recovers 92-99.8% of what any mode combination could reach…The Missing Complement: State-Conditioned Minimal Sufficient Evidence for Coding Agents
A coding agent halfway through an issue has already read much of what a retriever ranks highest.Think Thrice Before Reranking: Multi-perspective Evidence and Reasoning Integration for Text Reranking
Reasoning-based reranking with Large Language Models (LLMs) has shown promising improvements in text ranking.Reasoning Quality Matters: Combating Reasoning Collapse in LLM-based Embedding Learning
Large Language Models (LLMs) have recently shown strong potential for producing context-rich text embeddings for retrieval.MAGIC: Marginal-Guided Compression with Optimal Transport for Efficient Visual Document Retrieval
Recent visual document retrieval (VDR) systems such as ColPali use multi-vector page embeddings, in which patch-level vectors enable fine-grained evidence matching but incur substantial index…DUPAR: Dual-Path Conversational Retrieval via Speech Retriever with Cross-Turn Evidence Caching
Voice assistants grounded in external knowledge typically use automatic speech recognition (ASR) to transcribe speech queries before retrieving evidence from textual knowledge bases.LIGE-GR: A Smooth Leap from Ranking to Generative Recommendation in the LLM Era
The remarkable success of large language models (LLMs) has provided important inspiration for the next generation of recommender systems.PageRecall: Measuring Page Selection in Literature-Grounded Question Answering
We describe our system for LitTraceQA (GroundLM @ EMNLP 2026): given a research question, retrieve the relevant papers from a pool of 27,487, cite the page and the table or figure where the answer…Time-Aligned Evolving Concept Graphs for Scientific Relation Forecasting
Forecasting scientific relations can guide discovery by identifying promising connections before they emerge.Single-Token Expected-Value Scoring for Cold-Start Candidate Ranking
AI-assisted sourcing streamlines candidate review, reducing the administrative burden of manual screening for recruiters.