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

Aug 3

A Nonlinear Singular Value Theory for Neural Networks

arXiv:2605. 06938v2 Announce Type: replace-cross Abstract: Recently Brown et al.

By Brian Charles Brown, Mauricio Munoz, Robert Bridges, David Grimsman, Sean Warnick

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arXiv Machine Learning

Aug 3

Don't Contrast the Impossible: Region-Constrained Batching for Contrastive User Modeling on a Local Community Platform

arXiv:2607. 28971v1 Announce Type: cross Abstract: Contrastive learning is widely used for user modeling in large-scale recommender systems, where standard in-batch negatives implicitly assume universal exposure that any user can be shown any item.

By Seungho Han, Byeongchang Kim, Jin Yu

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arXiv AI

Aug 3

Guarantees on Dynamical System Distinguishability for LLM Token Generation

arXiv:2607. 28667v1 Announce Type: cross Abstract: Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a black-box dynamical system (DS) and comparing prediction residuals of two DSs.

By Mohamed Akrout, Dan Wilson

llms rag

arXiv AI

Aug 3

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

arXiv:2603. 11872v3 Announce Type: replace-cross Abstract: Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI systems lack direct access to transcriptomic representations while expression foundation models remain opaque to natural language.

By Omar Coser

llms rag agents

arXiv AI

Aug 3

Dimensionality reduction for homological stability and global structure preservation

arXiv:2503. 03156v4 Announce Type: replace-cross Abstract: We propose DiRe, a force-directed dimensionality reduction framework designed to preserve global structure and homological features while remaining practical on modern hardware.

By Alexander Kolpakov, Igor Rivin

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arXiv AI

Aug 3

Adjudicated Captioning: Multi-Agent Alignment Scoring and Consensus-Distilled Beam Arbitration for Strict Zero-Shot Image Captioning

arXiv:2607. 28986v1 Announce Type: cross Abstract: Zero-shot image captioning (ZIC) describes images without paired image-caption supervision during captioner training, relying on text-only corpora and frozen pretrained image-text scorers.

By Duy Tran Thanh, Thien-Phuc Doan, Long Nguyen-Vu, Ngo Tan Vu Khanh

llms rag agents efficiency multimodal safety

arXiv AI

Aug 3

TerraNova: A Foundation Model for the Anthropocene

arXiv:2607. 29527v1 Announce Type: cross Abstract: A defining problem of the Anthropocene is to model the physical Earth and human societies as one coupled system, yet no learned representation spans their observational breadth.

By Carlos Rodriguez-Pardo, Massimo Tavoni

llms rag multimodal safety

arXiv Machine Learning

Aug 3

Can LLMs Really Understand Item Difficulty Levels? Implications for Automated Item Generation Using LLMs

arXiv:2607. 28634v1 Announce Type: cross Abstract: The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments.

By Xinyi Wang, Hong Jiao, Ming Li, Sydney Peters, Hanna Choi, Tianyi Zhou, Qingshu Xu

llms rag

arXiv AI

Aug 3

Multi-Granularity Position Embedding of Graphs via Granular-Ball for Link Prediction

arXiv:2607. 29115v1 Announce Type: cross Abstract: Link prediction aims to identify potential or future connections within a given graph structure.

By Sen Zhao, Cheng Liu, Shuyin Xia, Zhiyuan Liu, Yi Liu, Yi Wang, Wei Wang

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arXiv Machine Learning

Aug 3

GALA: Generative Aligned Learning for Adaptive Multimodal Representation in the Taobao Shangou Recommender System

arXiv:2607. 29213v1 Announce Type: cross Abstract: Modern recommender systems in food delivery increasingly leverage multimodal signals, including images, text, and user interaction histories, to enhance user experience, yet effective fusion of these heterogeneous modalities remains challenging, hindering both the joint modeling of multimodal signals and adaptation to evolving user intent.

By Jiping Liu, Zhongmin Zhang, Zisen Sang, Zhijia Fang, Tao Ouyang, Ma Jiang, Shaopeng Liang, Zeyang Hou, Guodong Cao, Jia Jia

rag reinforcement-learning fine-tuning multimodal benchmarks safety

arXiv AI

Aug 3

DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Models

arXiv:2607. 28936v1 Announce Type: cross Abstract: Facial biometric identification relies on the distinctiveness of user attributes within a high-dimensional embedding space.

By Omid Ahmadieh, Nima Karimian

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arXiv AI

Aug 3

DragonCrawl: A Generative, Intent-Based Framework for Scalable Mobile End-to-End Testing

arXiv:2607. 28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cross-platform scalability.

By Sowjanya Puligadda, Mengdie Zhang, Ali Zamani, Dhruva Dixith Kurra, Eric Chen, Juan Marcano

llms rag agents multimodal

arXiv Machine Learning

Aug 3

Persistent Convolution: A Topological Framework for AI Alignment Testing and Semantic Space Characterization

arXiv:2607. 29008v1 Announce Type: cross Abstract: Modern opaque AI models prize performance over interpretability, which makes testing difficult.

By Tyler Ashoff, Jordan Rodu

rag multimodal safety

arXiv Machine Learning

Aug 3

Transpiler Autotuning with Predictive Models for Quantum Circuit Optimization

arXiv:2607. 29145v1 Announce Type: cross Abstract: Quantum software engineering is an emerging research field focusing on efficiently embedding the quantum programming paradigm into existing software ecosystems.

By Piotr Malkowski, Domenik Eichhorn, Joshua Ammermann, Rinor Kelmendi, Nick Poser, Patrick Hopf, Ina Schaefer

rag benchmarks

arXiv Machine Learning

Aug 3

Embedding of Low-Dimensional Sensory Dynamics in Recurrent Networks: Implications for the Geometry of Neural Representation

arXiv:2601. 19019v3 Announce Type: replace-cross Abstract: Neural population activity in sensory cortex is organized on low-dimensional manifolds, but why such manifolds arise and what determines their geometry remain unclear.

By Vikas N. O'Reilly-Shah, Alessandro Maria Selvitella

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arXiv Machine Learning

Aug 3

QASP: Query-Adaptive Robust Vector Search Policy

arXiv:2607. 29606v1 Announce Type: cross Abstract: A fundamental challenge of vector search is achieving consistently high recall while minimizing computational costs.

By Hakan Ferhatosmanoglu, Kushal Kumar, Tal Wagner, Andy Warfield

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arXiv AI

Aug 3

Have I Seen You? Embedding Behavior Signals Synthetic Face Dataset Membership

arXiv:2607. 29144v1 Announce Type: cross Abstract: Synthetic face datasets are increasingly used to reduce privacy exposure and data access constraints in biometric recognition.

By Pawe{\l} Borsukiewicz, Daniele Lunghi, Wendk\^uuni C. Ou\'edraogo, Jacques Klein, Tegawend\'e F. Bissyand\'e

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arXiv AI

Aug 3

Seeing Differently: Modeling Interpretive Perspectives in Computational Creativity using a Four-World Framework

arXiv:2607. 28644v1 Announce Type: cross Abstract: Creativity in computational systems is often evaluated as an objective property of artifacts, with existing Computational Creativity (CC) frameworks assessing creative merit at the level of outputs or systems rather than interpretive context.

By Prerna Luthra

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arXiv AI

Aug 3

Auto-JEPA: A Latent World Model of Continuous Intent for End-to-End Autonomous Driving

arXiv:2607. 29031v1 Announce Type: cross Abstract: Existing autonomous-driving world models typically perform dense prediction of future videos, occupancy states, BEV representations, or agent motion.

By Jiwei Yang, Zhengxian Chen, Chaosheng Huang, Jun Li

rag agents robotics

arXiv AI

Aug 3

Information Processing by Neuron Populations in the Central Nervous System: A Theory of the Mathematical Structure of Data and Operations

arXiv:2309. 02332v3 Announce Type: replace-cross Abstract: In the mammalian central nervous system, neurons are organized into populations communicating by spike trains propagating along axonal bundles.

By Martin N. P. Nilsson

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