Retrieval-augmented generation

Retrieval pipelines, vector search, chunking and reranking: how models are grounded in a corpus instead of their weights.

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arXiv AI

Jul 10

Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph

arXiv:2607. 08746v1 Announce Type: cross Abstract: While UMAP is widely used for exploring high-dimensional data, typical workflows focus on its lower-dimensional embedding, largely overlooking the rich k-nearest-neighbor (kNN) graph that UMAP constructs internally.

By Duen Horng Chau, Donghao Ren, Fred Hohman, Dominik Moritz

rag

arXiv AI

Jul 10

Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition

arXiv:2607. 08374v1 Announce Type: cross Abstract: Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological taxonomies rather than uncovering shared underlying behavioral structure.

By Jing Jie Tan, Ban-Hoe Kwan, Danny Wee-Kiat Ng, Yan-Chai Hum, Shih-Yu Lo, Po-An Chen, Noriyuki Kawarazaki, Kosuke Takano, Anissa Mokraoui

llms rag safety data-engineering

arXiv AI

Jul 10

PARA-PV: Physics-Aware Retrieval-Augmented PV Prediction Based on Frozen Foundation Model and Distribution Shift Correction

arXiv:2607. 08079v1 Announce Type: new Abstract: Accurate photovoltaic (PV) power forecasting is essential for reliable grid dispatch and renewable energy integration, yet it remains challenging because PV generation is jointly shaped by weather variability, day-night transitions, regime-dependent dynamics, and strict physical constraints.

By Hang Fan, Weican Liu, Ying Lu, Dunnan Liu, Long Cheng, Wei Wei

rag

arXiv Machine Learning

Jul 10

ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning

arXiv:2605. 30612v2 Announce Type: replace-cross Abstract: Continuous control policies trained with off-policy reinforcement learning frequently exhibit high-frequency action jitter, impractical for direct deployment on physical actuators.

By Faiq Shamass

rag reinforcement-learning efficiency

arXiv Machine Learning

Jul 10

A Self-Supervised Approach for Minimal-Annotation Hydroacoustic Data Exploration

arXiv:2607. 07733v1 Announce Type: cross Abstract: Passive hydroacoustic monitoring often generates large volumes of continuous recordings that are only partially exploited due to the cost of manual annotation.

By Pierre-Yves Raumer, Axel Marmoret, Dorian Cazau, Anatole Gros-Martial, Richard Dreo, Maelle Torterotot, Sara Bazin, Flore Samaran, Jean-Yves Royer

rag

arXiv Machine Learning

Jul 10

Improving RCT-Based Treatment Effect Estimation Under Covariate Mismatch via Calibrated Alignment

arXiv:2603. 19186v3 Announce Type: replace Abstract: Randomized controlled trials (RCTs) are the gold standard for estimating treatment effects, yet they are often underpowered for detecting effect heterogeneity.

By Amir Asiaee, Samhita Pal

rag safety

arXiv Machine Learning

Jul 10

Eigenvalue Calibration for Semantic Embeddings of Large Language Models

arXiv:2607. 08377v1 Announce Type: new Abstract: Uncertainty quantification is central to the reliable deployment of large language models (LLMs), and eigenvalues of semantic embeddings have recently emerged as a key tool in state-of-the-art methods.

By Sebastian G. Gruber, Nassim Walha, Francis Bach, Florian Buettner

llms rag benchmarks

arXiv AI

Jul 10

VectorizationLLM: Smart Vectorization Based AI Assistant

arXiv:2607. 07846v1 Announce Type: new Abstract: VectorizationLLM is a specialized Large Language Model based on Google open-weight LLMs.

By Ryan Duke

llms rag

arXiv Machine Learning

Jul 10

Stochastic Order Learning: An Approach to Rank Estimation Using Noisy Data

arXiv:2607. 08103v1 Announce Type: new Abstract: Rank estimation under label noise poses a fundamental challenge, as ordinal annotations often exhibit structured uncertainty rather than simple label corruption.

By Chaewon Lee, Seon-Ho Lee, Chang-Su Kim

rag

arXiv AI

Jul 10

DeepTutor: Towards Agentic Personalized Tutoring

arXiv:2604. 26962v3 Announce Type: replace-cross Abstract: Education is one of the most promising real-world applications for Large Language Models (LLMs).

By Bingxi Zhao, Jiahao Zhang, Xubin Ren, Zirui Guo, Tianzhe Chu, Yi Ma, Chao Huang

llms rag agents benchmarks safety

arXiv AI

Jul 10

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE

arXiv:2607. 07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workflows whose accumulated reasoning and tool traces routinely push the input an order of magnitude past the pretraining window, making zero-shot context extension the dominant deployment path for open-weight checkpoints.

By Haozhan Tang, Zerui Wang, Yuxian Gu, Song Han, Han Cai

llms rag agents efficiency benchmarks

arXiv Machine Learning

Jul 10

BACH: A Bayesian Admixture of Contrastive Heads for Multi-Interest Two-Tower Retrieval

arXiv:2607. 08107v1 Announce Type: cross Abstract: Two-tower retrievers compress each user into a single embedding, limiting their ability to serve diverse interests.

By Quoc Phong Nguyen, Paul Albert, Long Vuong, Vuong Le, Julien Monteil

rag benchmarks

arXiv Machine Learning

Jul 10

MatBind: A Shared Embedding Space for Multimodal Materials Characterization

arXiv:2607. 08470v1 Announce Type: new Abstract: Fully characterizing a crystalline material requires integrating heterogeneous data sources -- atomic structures, diffraction patterns, electronic density of states, and natural language -- each of which captures a different facet of the same physical object.

By Le Yang (Institute for Advanced Simulations), Anoop K. Chandran (J\"ulich Supercomputing Centre, Forschungszentrum J\"ulich), Jona \"Ostreicher (Institute of Nanotechnology, Karlsruhe Institute of Technology), Evgenii Sovetkin (J\"ulich Supercomputing Centre, Forschungszentrum J\"ulich), Adrian Mirza (Helmholtz-Zentrum Berlin f\"ur Materialien und Energie, Helmholtz Institute for Polymers in Energy Applications Jena), Sebastien Bompas (Institute for Advanced Simulations), Bashir Kazimi (Institute for Advanced Simulations), Pascal Friederich (Institute of Nanotechnology, Karlsruhe Institute of Technology), Stefan Kesselheim (J\"ulich Supercomputing Centre, Forschungszentrum J\"ulich, 1. Physikalisches Institut, University of Cologne), Kevin Maik Jablonka (Helmholtz Institute for Polymers in Energy Applications Jena, Center for Energy and Environmental Chemistry Jena, Friedrich Schiller University Jena), Stefan Sandfeld (Institute for Advanced Simulations, Faculty 5 - Georesources and Materials Engineering, RWTH Aachen University)

rag multimodal safety

arXiv AI

Jul 10

PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs

arXiv:2607. 08269v1 Announce Type: new Abstract: Existing retrieval-augmented generation (RAG) systems treat web pages as flat text, losing the structural and semantic signals encoded in HTML.

By Ying Liu, Yi Ye, Quanyu Feng, Mingxi Ye, Mingtao Zhang, Haoyang Li, Chen Jason Zhang, Qing Li

llms rag benchmarks

arXiv AI

Jul 10

MetaHGNIE: Meta-Path Induced Hypergraph Contrastive Learning in Heterogeneous Knowledge Graphs

arXiv:2512. 12477v2 Announce Type: replace Abstract: Estimating node importance in heterogeneous knowledge graphs is a fundamental problem underlying recommendation, search, and knowledge decision systems.

By Jiawen Chen, Yanyan He, Qi Shao, Mengli Wei, Duxin Chen, Wenwu Yu, Yanlong Zhao

llms rag benchmarks safety

arXiv AI

Jul 10

A Multi-cluster Boundary Learning Method for Out-of-Scope Intent Detection via MiniLM Embedding

arXiv:2607. 07974v1 Announce Type: cross Abstract: Intent detection is a critical task that bridges human intents and system actions in human-machine interaction systems.

By Yihong Xu, Mingyu Kang, Linyuan L\"u

llms rag benchmarks

arXiv AI

Jul 10

The Context Access Divide: Interaction-Level Architecture as a Complementary Dimension of Agentic Inequality

arXiv:2607. 08495v1 Announce Type: cross Abstract: Sharp et al.

By Masahiro Fujita

rag agents

arXiv AI

Jul 10

Applying JEPA-Style Predictive Learning to JA4-Derived Network Fingerprints

arXiv:2607. 08465v1 Announce Type: new Abstract: I-JEPA and V-JEPA learn by matching latent predictions to target encoder outputs rather than regenerating the original input, and this has worked well for images and video.

By Javier Izquierdo, Aygul Zagidullina

llms rag

arXiv Machine Learning

Jul 10

The Proxy Presumption: From Semantic Embeddings to Valid Social Measures

arXiv:2605. 07409v2 Announce Type: replace-cross Abstract: Natural Language Processing is rapidly evolving into a primary instrument for Computational Social Science, with researchers increasingly using embeddings to measure latent constructs such as novelty, creativity, and bias.

By Baishi Li, Ta Yu, Kelvin J. L. Koa, Ke-Wei Huang

llms rag nlp safety

arXiv AI

Jul 10

Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text

arXiv:2607. 08490v1 Announce Type: new Abstract: Biomedical language evolves rapidly as new discoveries emerge, causing traditional text models to lose semantic fidelity over time.

By Bharathwaj Vijayakumar, Sahana K. Varadaraju

rag

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