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 7

Quick ViTs: Speeding up Vision Transformers through Equivariance

arXiv:2505. 15441v5 Announce Type: replace-cross Abstract: Natural images exhibit strong geometric regularities: local structures, such as edges, corners, and textures, appear in many orientations and mirror configurations.

By David Nordstr\"om, Johan Edstedt, Fredrik Kahl, Georg B\"okman

llms rag efficiency

arXiv Machine Learning

Jul 7

MABLE: Masked Autoencoding with Bi-Lipschitz Decoding for Embeddings and Graph Metric Learning

arXiv:2607. 02990v1 Announce Type: new Abstract: We propose MABLE (Masked Autoencoding with Bi-Lipschitz Decoding for Embeddings and Graph Metric Learning), a self-supervised framework for learning node and graph embeddings from large, heterogeneous graphs, demonstrated here on geospatial mineral-exploration data.

By Yaniv Shulman, Shaghayegh Akbarpour, Jack B. Muir

rag safety

arXiv AI

Jul 7

Unified Audio Intelligence Without Regressing on Text Intelligence

arXiv:2607. 05196v1 Announce Type: cross Abstract: Audio intelligence involves understanding, reasoning about, and generating both audio and speech.

By Zhifeng Kong, Sang-gil Lee, Jaehyeon Kim, Boxin Wang, Zihan Liu, Sungwon Kim, Yang Chen, Arushi Goel, Rajarshi Roy, Wenliang Dai, Zhuolin Yang, Yangyi Chen, Dongfu Jiang, Sreyan Ghosh, Tuomas Rintamaki, Andrew Tao, Jonathan Raiman, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping

llms rag agents reinforcement-learning efficiency multimodal benchmarks safety

arXiv Machine Learning

Jul 7

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling

arXiv:2607. 04409v1 Announce Type: new Abstract: Learning and planning in imagination using world models provides an effective paradigm for training agents for decision-making.

By Fan Feng, Yujia Zheng, Minghao Fu, Yongqiang Chen, Guangyi Chen, Kevin Murphy, Biwei Huang, Kun Zhang

rag agents robotics benchmarks

arXiv AI

Jul 7

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

arXiv:2607. 04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does not indicate which sentence is unsupported, or why.

By Mohamed Aly Bouke

rag nlp benchmarks safety

arXiv AI

Jul 7

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

arXiv:2607. 02632v1 Announce Type: cross Abstract: Time-series forecasting supports decisions in finance, en-ergy, transportation, public health, and industrial monitoring.

By Shah Nawaz Haider, Steve Austin, Arnab Barua, Sarowar Morshed Shawon, Hadaate Ullah

llms rag safety

arXiv AI

Jul 7

A Retrieval-Augmented Framework for Detecting and Resolving Pragmatic Ambiguities in Natural Language Requirements

arXiv:2607. 04436v1 Announce Type: cross Abstract: Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development.

By Pavithra PM Nair, Preethu Rose Anish

llms rag safety

arXiv Machine Learning

Jul 7

Deriving Benchmarking Datasets from Long-Form Recordings: Challenges and Opportunities

arXiv:2607. 03201v1 Announce Type: cross Abstract: Long-form recordings (LFRs) of child-centered audio are ecologically valid sources for studying early language development, but three problems limit their use.

By Kaveri K. Sheth, Lawrence Borst, Tarek Kunze, Marvin Lavechin, Okko R\"as\"anen, Sho Tsuji, Loann Peurey, Alix Bourr\'ee, Alejandrina Cristia

rag benchmarks safety

arXiv AI

Jul 7

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System

arXiv:2607. 04993v1 Announce Type: cross Abstract: Many phenomena of deep learning are dynamical: they concern not only which minima exist, but how gradient descent reaches, avoids, or selects among them.

By Thomas Hofmann

rag safety

arXiv Machine Learning

Jul 7

When Style Similarity Scores Fail: Diagnosing Raw CSD Cosine in Artist-Style Evaluation

arXiv:2605. 09030v2 Announce Type: replace-cross Abstract: Raw cosine in the 768-dimensional output space of the Contrastive Style Descriptor (CSD) is now widely read as an absolute, calibrated style-fidelity score for text-to-image and style-imitation evaluation.

By J\"org Frochte

rag diffusion

arXiv Machine Learning

Jul 7

Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls

arXiv:2607. 03515v1 Announce Type: cross Abstract: In many machine learning applications, the most relevant items for a query should be efficiently retrieved.

By Kirill Shevkunov, Andrey Ploskonosov, Liudmila Prokhorenkova

rag

arXiv AI

Jul 7

EventCoT: Event-centric Video Chain-of-thought for Reasoning Temporal Localization

arXiv:2607. 04872v1 Announce Type: cross Abstract: Reasoning temporal localization (RTL) requires a model to generate an answer that itself contains the time interval supporting it, so high-level reasoning and precise temporal grounding must be produced jointly in a single response.

By Youngkil Song, Yoonjae Baek, Dongwon Kim, Inho Kim, Dongkeun Kim, Suha Kwak

rag nlp benchmarks

arXiv AI

Jul 7

MoP-JEPA: Hard-Assigned Predictor Mixtures for Stochastic JEPA World Models

arXiv:2607. 05238v1 Announce Type: new Abstract: JEPA world models predict the next latent state with a single deterministic predictor trained by latent regression.

By Zhi Song, Ximing Xing, Zhenchao Tang, hanbo Huang, Tianxu Lv, minghao Yang, Zhongzheng Niu, He Bing, Lusheng Wang, Jianhua Yao

rag multimodal

arXiv Machine Learning

Jul 7

GlaKG: A Biomarker-Centric Fundus Knowledge Graph for Explainable Glaucoma Diagnosis and Risk Assessment

arXiv:2607. 04673v1 Announce Type: cross Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer little clinical interpretability.

By Cheng Huang, Jia Zhang, Yi Jiang, Yang Liu, Karanjit Kooner, Yadi Liu, Tsengdar Lee, Yang Xie, Wenqi Shi, Guanghua Xiao

rag safety

arXiv AI

Jul 7

MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems

arXiv:2605. 28732v2 Announce Type: replace-cross Abstract: Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult to debug.

By Xinle Deng, Ruobin Zhong, Hujin Peng, Xiaoben Lu, Yanzhe Wu, Guang Li, Buqiang Xu, Yunzhi Yao, Jizhan Fang, Haoliang Cao, Junjie Guo, Yuan Yuan, Ziqing Ma, Yuanqiang Yu, Rui Hu, Baohua Dong, Hangcheng Zhu, Ningyu Zhang

llms rag benchmarks

arXiv AI

Jul 7

Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion

arXiv:2607. 03154v1 Announce Type: cross Abstract: Multi-domain knowledge graph completion (MKGC) aims to improve missing triple prediction in a target KG by transferring knowledge from other support KGs.

By Jiawei Sheng, Taoyu Su, Xixun Lin, Xiaodong Li, Tingwen Liu

rag diffusion benchmarks

arXiv AI

Jul 7

CaresAI at SMM4H-HeaRD 2026: Predicting TNM Staging

arXiv:2607. 03466v1 Announce Type: cross Abstract: This study aims to predict Tumor, Node, and Metastasis (TNM) stage labels independently, with the Cancer Genome Atlas (TCGA) pathology report as the sixth shared task of SMM4H-HeaRD 2026.

By Joseph Itopa Abubakar, Jorge Jarme, Favour Igwezeke, Mary Adewunmi

rag

arXiv Machine Learning

Jul 7

Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control

arXiv:2607. 04978v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) underpin a growing family of latent world models for control from raw pixels, but every existing JEPA world model commits at training time to a single inference paradigm: either trajectory optimisation in a learned dynamics model, or direct behaviour cloning.

By Ruslan Rakhimov, George Bredis, Yuriy Maksyuta, Daniil Gavrilov

rag diffusion benchmarks

arXiv Machine Learning

Jul 7

From Interaction to Intent: Inferring User Objectives from Provenance Logs

arXiv:2607. 04501v1 Announce Type: cross Abstract: The ability to automatically infer analytic intent from user interaction histories could enable interactive AI systems to proactively assist users during exploratory data analysis.

By Steffen Holter, Tobias St\"ahle, Arpit Narechania, Mennatallah El-Assady

rag

arXiv Machine Learning

Jul 7

Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models

arXiv:2602. 24264v2 Announce Type: replace-cross Abstract: Compositional generalization, the ability to recognize familiar parts in novel contexts, is a defining property of intelligent systems.

By Arnas Uselis, Andrea Dittadi, Seong Joon Oh

rag

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