All entries

MARS: Multi-Agent Re-ranking for Repeat-Order Food Delivery Recommendation

arXiv:2607.25420v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in recommender systems, but it is often unclear how much performance can be obtained from strong pr

local-aiarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Matrix-Free Photoacoustic Image Reconstruction via Sensor-Token Self-Attention

DGX agent

arXiv:2607.25576v1 Announce Type: new Abstract: Photoacoustic tomography (PAT) combines the optical absorption contrast of biological tissue with the spatial resolution of ultrasound, yet recovering t

researcharxiv-cs-ai

29 Jul 2026

Agents

Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering

arXiv:2607.25090v1 Announce Type: new Abstract: Machine learning engineering (MLE) tasks require long-horizon decision making over iterative solution debugging and refinement, under expensive and feed

agentsarxiv-cs-ai

Hardware

MDTransformer: A Hardware-Software Co-Design of Mode-Division Photonic Transformer Accelerator with Inverse-Designed Coherent Crossbar

arXiv:2607.26016v1 Announce Type: cross Abstract: Recently, photonic transformer accelerators (PTAs) have successfully achieved significant speedup and energy efficiency improvements over electronic a

hardwarearxiv-cs-ai

Measuring and Improving Behavioral Consistency in Large Language Models through Fact-Heuristic-Emotion State Enforcement

arXiv:2607.24765v1 Announce Type: cross Abstract: Large language models (LLMs) can give different answers to the same decision problem across runs, and reverse a decision when their own prior answer r

Measuring the State of Open Science in Transportation Using Large Language Models

arXiv:2601.14429v2 Announce Type: replace-cross Abstract: Open science initiatives have strengthened scientific integrity and accelerated research progress across many fields, but the state of their p

Mechanisms of Width Scaling in Normalized Residual Networks: The Effective Alignment Dimension

arXiv:2607.24887v1 Announce Type: cross Abstract: Existing theories of neural-network width characterize asymptotic limits, but provide limited guidance on whether an expansion direction identified fr

Med-R^3: Enhancing Medical Retrieval-Augmented Reasoning of LLMs via Progressive Reinforcement Learning

arXiv:2507.23541v5 Announce Type: replace Abstract: In medical scenarios, effectively retrieving external knowledge and leveraging it for rigorous logical reasoning is of significant importance. Despi

Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation

arXiv:2602.10508v2 Announce Type: replace Abstract: Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting our ability to diagnose failures, understand da

safetyarxiv-cs-cv

MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence

arXiv:2603.27176v2 Announce Type: replace Abstract: Lesion detection, symptom tracking, and visual explainability are central to real-world medical image analysis, yet current medical Vision-Language

applicationsarxiv-cs-cv

Medical world models in healthcare: foundations, applications, and challenges for trustworthy clinical translation

arXiv:2607.25242v1 Announce Type: new Abstract: Medical world models offer a framework for extending medical artificial intelligence beyond static prediction by representing evolving patient states an

safetyarxiv-cs-cv

MEDit-Bench: A Dataset for Evaluating Message-Driven Narrative Video Editing

model-releasesarxiv-cs-cv

arXiv:2607.25300v1 Announce Type: new Abstract: Video editing is fundamentally message-driven: even from the same source footage, the selected shots change depending on the narrative the editor wishes

MedJudgeRAG: Option-Wise Evidence Judgment with Dynamic Knowledge Graphs for Medical MCQA

arXiv:2607.24838v1 Announce Type: cross Abstract: In medical multiple-choice question answering (MCQA), Retrieval-Augmented Generation (RAG) can supplement the domain knowledge of language models (LMs

MemLens: A Value-Aware Memory Management System with Interactive Analytics for LLM-based Agents

arXiv:2607.25992v1 Announce Type: cross Abstract: Recently, memory management has become a key infrastructure for LLM-based agents, as it directly affects long-horizon reasoning, personalized response

Memory for Large Language Models

arXiv:2607.25380v1 Announce Type: new Abstract: Memory has evolved into a foundational architectural dimension in large language models (LLMs), shifting from an implicit byproduct of computation to a

Memory Layer: Train the In-Model Cache for Recommendation Models

arXiv:2607.25110v1 Announce Type: cross Abstract: Early ranking stages in recommendation systems precompute item embeddings and cache them in-model for scoring within strict latency constraints. Becau

applicationsarxiv-cs-lg

MemSFT: Mitigating Alignment Tax with an External Parametric Memory

arXiv:2607.25614v1 Announce Type: cross Abstract: Adapting Large Language Models (LLMs) to specialized domains often incurs an alignment tax, as fine-tuning on domain-specific tasks can cause catastro

Messier: A High-Resolution Corpus for Cross-Benchmark Agent Evaluation

arXiv:2607.25891v1 Announce Type: new Abstract: Evaluating AI agents in interactive environments is hindered by fragmented tasks, scaffolds, verifiers, and scoring rules. Existing efforts focus on nar

Mind the Missing Split: Resolving Feature Heterogeneity in Swarm Learning with Random Forests

arXiv:2607.25538v1 Announce Type: new Abstract: Swarm Learning is a decentralized collaborative learning mechanism that allows multiple organizations to train a shared model without central coordinati

local-aiarxiv-cs-lg

Minimizing Targeted Activations: Input-Only Suppression of Evaluation-Awareness Latents in Large Language Models

arXiv:2607.25907v1 Announce Type: cross Abstract: Activation steering controls model behavior by editing internal activations at inference time. We study its input-side dual: optimizing a fluent promp

Modular Robotic Catheters for Endovascular Aneurysm Repair

arXiv:2607.25807v1 Announce Type: new Abstract: Fenestrated/Branched endovascular aneurysm repair (FEVAR/BEVAR) require surgeons to navigate catheters and guidewires into various branches of the abdom

researcharxiv-cs-ro

MODUS: Decoder-Only Any-to-Any Modeling of Diverse Modalities

arXiv:2607.25948v1 Announce Type: cross Abstract: Any-to-any models predict any modality from any combination of others within a single network, a formulation used in multimodal vision and vision-lang

Mondrian: On-Device High-Performance Video Analytics with Compressive Packed Inference

arXiv:2403.07598v2 Announce Type: replace Abstract: In this paper, we present Mondrian, an edge system that enables high-performance object detection on high-resolution video streams. Many lightweight

local-aiarxiv-cs-cv

MorphUNet: Alpha-Controlled Biometric Transport for Diffusion-Based Face Morphing Attacks

model-releasesarxiv-cs-cv

arXiv:2607.25092v1 Announce Type: new Abstract: Face morphing attacks create synthetic images verifiable against multiple identities, threatening border control and identity verification systems. We i

MOSAIC-FL, a micro-service based privacy-preserving framework with application to genomics

arXiv:2607.25107v1 Announce Type: cross Abstract: Security and privacy are primordial requirements for Federated Learning (FL), especially in fields such as healthcare and genomics where sensitive inf

applicationsarxiv-cs-lg

Motion-Acceleration Calibration and Compensation in IMUs without External Equipment for Attitude Estimation Filters

arXiv:2607.25784v1 Announce Type: new Abstract: Attitude estimation based on inertial sensing requires measurements of local angular velocities and local gravity via gyroscopes and accelerometers. How

safetyarxiv-cs-ro

Motion Generation With Environmental Constraints

arXiv:2607.25053v1 Announce Type: new Abstract: Robot motion planning faces challenges in high-dimensional spaces and uncertain environments, often constrained by the need for collision-free motions.

safetyarxiv-cs-ro

Multi-Fidelity Learning with Shallow Recurrent Decoders for Multi-Physics Applications

model-releasesarxiv-cs-lg

arXiv:2606.05202v2 Announce Type: replace-cross Abstract: In reactor physics, neutronics and multi-physics phenomena can be modelled at different fidelity levels. High-fidelity models based on the Bol

Multi-Objective Kinodynamic Motion Planning with Asymptotic Pareto Optimality

arXiv:2607.15508v2 Announce Type: replace Abstract: In this paper, we address the challenge of multi-objective motion planning for systems under kinodynamic constraints. We consider three problem clas

researcharxiv-cs-ro

Multi-Scale Structural Features for Continual, Comprehensible Visual Recognition in a Developmental Learning Framework

arXiv:2607.25531v1 Announce Type: cross Abstract: Contemporary machine learning struggles to learn continually, reuse prior knowledge, and expose a comprehensible internal structure. A recently propos

Multi-Sensor Alignment for Weather Simulations

arXiv:2607.25612v1 Announce Type: new Abstract: Perception tasks for autonomous vehicles need to work satisfactorily in adverse weather conditions. Due to lack of real-world weather datasets, weather

safetyarxiv-cs-ai

Multiclass Classification without Labels via Posterior Simplex Geometry

arXiv:2607.24943v1 Announce Type: cross Abstract: In many classification problems, reliable instance-level labels are unavailable. However, it is often possible to construct weakly enriched unlabeled

Multimodal Hybrid Retrieval-Augmented Generation for Scientific Document Understanding using Open-Source SLMs

arXiv:2607.24799v1 Announce Type: cross Abstract: Large Language Models tend to hallucinate when answering domain-specific ques tions from scientific documents without prior fine-tuning. Currently, me

MusiChat: Vibe Composing for Music Creation

arXiv:2607.24873v1 Announce Type: new Abstract: Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts. However, most existing system

MyMentorLLM: A psychotherapy GenAI environment with multimodal voice/text patients, trainees and experts for deliberate practice

arXiv:2607.25667v1 Announce Type: cross Abstract: Psychotherapists need repeated training and supervision by experts; however, scalability is problematic. Here we present MyMentorLLM, a multimodal voi

MyoCardBench: A Real-World Data Benchmark for Evaluating Large Language Models in Clinically Authentic Cardiovascular Care Scenarios

arXiv:2607.25186v1 Announce Type: new Abstract: Background: Most medical large language model (LLM) benchmarks focus on examination knowledge or isolated tasks and may not reflect the longitudinal, mu

Agents

Nanobot Algorithms for Treatment of Diffuse Cancer

arXiv:2509.06893v2 Announce Type: replace-cross Abstract: Motile nanosized particles, or 'nanobots', promise more effective and less toxic targeted drug delivery because of their unique scale and prec

agentsarxiv-cs-ro

Neurai-VN Benchmark: Standardized Machine Learning Models for Multimodal Digital Phenotyping in Mental Health Classification

model-releasesarxiv-cs-lg

arXiv:2607.25232v1 Announce Type: new Abstract: Digital phenotyping (DP) using smartphones and wearable devices has shown considerable potential for mental health monitoring. However, progress remains

Neural Network Learning of One-Bit Protocols for Qubit Measurement Simulation

arXiv:2607.23645v1 Announce Type: cross Abstract: Communication complexity provides a natural framework for quantifying the classical resources required to reproduce quantum statistics. In the qubit p

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising

arXiv:2607.24841v1 Announce Type: new Abstract: Autoregressive (AR) large language models (LLMs) are inherently inefficient at inference time because each generated token requires accessing the full s

NEXT: Reasoning-Driven Video Recommendation via a Vision-Language Model

arXiv:2607.24789v1 Announce Type: cross Abstract: We present NEXT (Next-interest EXploration Transformer), a reasoning-driven video recommendation framework that reasons over the video a user has just

safetyarxiv-cs-cv

Noise-Free One-Step LoRA for Task-Driven Image Restoration with Diffusion Priors

arXiv:2607.25390v1 Announce Type: new Abstract: Degraded images not only reduce visual quality but also impair downstream high-level vision tasks. Task-driven image restoration (TDIR) addresses this i

applicationsarxiv-cs-cv

Tutorials

Normalizing Flows to Reconstruct Pseudo-PDFs

arXiv:2607.25282v1 Announce Type: cross Abstract: We investigate a normalizing-flow approach for reconstructing parton distribution functions (PDFs) from synthetic matrix-element data. Our framework c

tutorialsarxiv-cs-lg

Nudging Sustainable Choices through LLM-Generated Recommendation Explanations

arXiv:2607.25726v1 Announce Type: new Abstract: Recommender systems mediate everyday consumption, offering a promising channel for encouraging sustainable choices. Prior research shows that explanatio

ObliCity: A Benchmark and Baseline for Roof-to-Ground Projection Displacement Correction

model-releasesarxiv-cs-cv

arXiv:2607.25210v1 Announce Type: new Abstract: Oblique-view urban remote sensing imagery inevitably exhibits geometric projection displacements between building roofs and footprints, leading to signi

Observing sycophantic AI validate others reduces its appeal but not its persuasiveness

arXiv:2607.25166v1 Announce Type: new Abstract: AI chatbots can be ``sycophantic,'' or overly agreeable and flattering toward users. Sycophantic AI has been shown to entrench attitudes, yet users freq

ODYSSE: Episode-wise Policy Optimization for Personalized Agentic Reasoning

arXiv:2607.25369v1 Announce Type: new Abstract: Agentic systems have rapidly advanced in their ability to interact with real-world environments, leverage external tools, and provide services for users

safetyarxiv-cs-ai

OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs

arXiv:2607.25669v1 Announce Type: new Abstract: Emerging Omni-modal Large Language Models (OmniLLMs) enable unified understanding of text, audio, and video, but their long audio-video token sequences

local-aiarxiv-cs-ai