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arXiv:2505.13099v3 Announce Type: replace Abstract: Vision Foundation Models (VFMs) have made remarkable progress and are increasingly being applied to segmentation tasks in real-world industrial sett

applicationsarxiv-cs-cv

InsightEmb: Learning Action-Intent Embeddings for Agentic Insight Retrieval

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DGX agent

arXiv:2608.04761v1 Announce Type: cross Abstract: Self-improving agents accumulate reusable insights from prior trajectories, making retrieval increasingly important for turning accumulated experience

model-releasesarxiv-cs-ai

6 Aug 2026

Integrated Noise and Safety Management in UAM via A Unified Reinforcement Learning Framework

arXiv:2508.16440v2 Announce Type: replace-cross Abstract: Urban Air Mobility (UAM) envisions the widespread use of small aerial vehicles to transform transportation in dense urban environments. Howeve

Agents

Interoceptive Attention as Dynamic Homeostatic Prioritization in a Foraging Agent

arXiv:2608.04232v1 Announce Type: new Abstract: Biological systems must regulate competing needs under limited perceptual bandwidth, where sharpening one estimate costs the capacity to sharpen the oth

agentsarxiv-cs-ai

Interpretable Fuzzy Inference for UAV Target Tracking Using Bounding-Box Geometry

arXiv:2608.04121v1 Announce Type: cross Abstract: Vision-based guidance of unmanned aerial vehicles (UAVs) toward unmanned ground vehicles (UGVs) supports cooperative aerial--ground robotics, but reli

local-aiarxiv-cs-ai

Interpreting GFlowNets for Drug Discovery: What probes can and cannot show

arXiv:2511.19264v2 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) construct molecules through sequential decisions, but their internal policies remain opaque, limiting ado

safetyarxiv-cs-ai

Tutorials

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds

arXiv:2608.04827v1 Announce Type: cross Abstract: We introduce the Intrinsic Hybrid Latent Diffusion Model (ILDM), a generative framework that integrates probabilistic dimensionality reduction with ge

tutorialsarxiv-cs-lg

InvFlowFD: Reference-Free and Background-Set-Free Perceptual Music Quality Metric with Flow Matching Inversion

arXiv:2608.04142v1 Announce Type: cross Abstract: Existing reference-free methods for evaluating music perceptual quality alleviate the need for paired noisy-clean data, but they still rely on a backg

IRIS: A Visual Cortex-Inspired Framework for Analyzing Orientation Selectivity in Vision Transformers

arXiv:2608.05122v1 Announce Type: new Abstract: Vision transformers (ViTs) have become the de facto standard for image encoding across many perception tasks. Despite their empirical success, it remain

local-aiarxiv-cs-cv

Agents

Is Monitoring Enough? Strategic Agent Selection For Stealthy Attack in Multi-Agent Discussions

arXiv:2603.21194v2 Announce Type: replace-cross Abstract: Multi-agent discussions have been widely adopted, motivating growing efforts to develop attacks that expose their vulnerabilities. In this wor

agentsarxiv-cs-ai

IslamicTurathBench: A Multi-Task, Multi-Discipline Benchmark for Evaluating Large Language Models on the Islamic Scholarly Tradition (turath)

arXiv:2608.04703v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for question answering, education, and research, including in religious and cultural domains where an

iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data

arXiv:2608.04348v1 Announce Type: cross Abstract: Multimodal learning of images and tabular data is often impaired by ineffective representations, resulting in redundancy, dispersion, and generalizati

Item Response Theory for AI Safety

arXiv:2608.05086v1 Announce Type: new Abstract: Language models differ in how safely they behave and these differences are measured by safety benchmarks. But aggregated benchmark scores are hard to tr

Joint UAV Flight and Opportunistic Routing under Reinforcement Learning for Delay-Tolerant Networks

arXiv:2608.04590v1 Announce Type: new Abstract: The growing deployment of delay-tolerant networks (DTNs) has made store-carry-forward (SCF) communication indispensable under sparse connectivity. Howev

safetyarxiv-cs-ai

K-EXAONE 2.0 Technical Report

arXiv:2608.04505v1 Announce Type: new Abstract: This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward glo

Kathleen Writes: Autoregressive Generation and Data Scaling Without Attention

arXiv:2608.04678v1 Announce Type: new Abstract: Papers 1-2 of the Kathleen series showed that a byte-level, attention-free architecture built from a wavetable encoder and multi-scale reverberant state

Kitchen Robotic Manipulation utilizing Foundation Models

model-releasesarxiv-cs-ro

arXiv:2608.04042v1 Announce Type: new Abstract: Deploying robots in everyday human environments requires perception systems that are both robust and adaptable to diverse, dynamic conditions. In this w

Koopman-Based Nonlinear Identification and Model Predictive Control of a Turbofan Engine

arXiv:2604.01730v2 Announce Type: replace Abstract: This paper investigates Koopman operator-based approaches for multivariable control of a two-spool turbofan engine. A physics-based component-level

researcharxiv-cs-lg

Label-Free Target-Domain Adaptation for Unconstrained Event-Image Feature Matching via Dual-Stage Distillation

model-releasesarxiv-cs-cv

arXiv:2607.10082v2 Announce Type: replace Abstract: Building pixel-level correspondence between event and image data is a fundamental task for multi-sensor systems. However, existing cross-modal match

Language Models Generalize to Human-like Word Order Preferences

arXiv:2608.05028v1 Announce Type: new Abstract: A central question in language acquisition is whether linguistic biases can emerge from general learning mechanisms operating over underdetermined input

safetyarxiv-cs-cl

LaPrune: Controllable Differentiable Sparsity at Million Scale

arXiv:2608.04057v1 Announce Type: cross Abstract: Top-k selection determines which components of a sparse model remain active. Hard selection blocks gradients, while continuous relaxations often coupl

Large Language Models for Low-Resource Languages: A Conceptual Framework for an Electronic Explanatory Dictionary of the Tajik Language

arXiv:2608.04186v1 Announce Type: new Abstract: This paper presents a conceptual framework for developing an electronic explanatory dictionary of the Tajik language using large language models (LLMs).

Large-Small Model Collaboration for Enhancing Edge-Deployed Small Models

arXiv:2503.10367v2 Announce Type: replace-cross Abstract: Edge devices host domain-specific small language models (SLMs) with limited resources, while private clouds offer larger LLMs. We propose G-Bo

Leak-Resistant Unlearning: A New Benchmark for Evaluating Multi-Hop Reasoning Consistency and Recovery Robustness

arXiv:2608.04519v1 Announce Type: new Abstract: Benchmarking machine unlearning methods is critical to understand whether sensitive knowledge is removed from large language models (LLMs) or not. Curre

Applications

Learning Compression Rules for Network Traffic

arXiv:2608.04545v1 Announce Type: new Abstract: We study the problem of learning compact rule-based compressors for structured network traffic. Each packet is a record of header fields that are highly

applicationsarxiv-cs-lg

Learning Neural Networks by Neuron Pursuit

arXiv:2509.12154v2 Announce Type: replace Abstract: The first part of this paper studies the evolution of gradient flow for homogeneous neural networks near a class of saddle points exhibiting a spars

researcharxiv-cs-lg

Agents

Learning Sexism Detection Using Multi-Agent Perspectivist Preference Optimization

arXiv:2608.04056v1 Announce Type: new Abstract: When people label text for sexism, they often disagree, and not because some of them are wrong: they genuinely perceive sexism differently. Most NLP sys

agentsarxiv-cs-cl

Learning to Resolve Neutron Resonances with Fully Convolutional Neural Networks

arXiv:2608.04027v1 Announce Type: new Abstract: This work investigates the feasibility of augmenting traditional R-Matrix codes with a robust machine learning framework for automatically detecting neu

Learning When to Stop: Prefix-Optimal Dynamic Diffusion Policies for Continuous Control

arXiv:2608.05084v1 Announce Type: new Abstract: Diffusion policies are a powerful policy class for continuous control, but their iterative denoising process creates a substantial computational bottlen

Lesion Detection in CT with Frozen Self-Distilled Features: SALT, a Spatially Adaptive Label-Guided Temperature

arXiv:2608.05100v1 Announce Type: new Abstract: Self-supervised pretraining objectives are spatially uniform: the teacher temperature and the per-patch loss weight are identical everywhere in the imag

safetyarxiv-cs-cv

Leveraging Interpretable Tsetlin Machine for PDF Malware Detection

arXiv:2607.09290v2 Announce Type: replace-cross Abstract: In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents du

local-aiarxiv-cs-lg

Leveraging Machine Learning to Gain Insights on Quantum Thermodynamic Entropy

arXiv:2305.06177v1 Announce Type: cross Abstract: We present a thermodynamic analysis of a quantum engine that uses a single quantum particle as its working fluid, inspired by Szilard's classical sing

researcharxiv-cs-cl

LiNC: Lightweight Noise Correction via Per-Sample Trust and Gaussian Mixture Modeling

arXiv:2608.04147v1 Announce Type: cross Abstract: Label noise is common in medical imaging datasets due to factors such as inter-rater variability, annotation errors, and ambiguous cases. This can sev

Lindblad-Inspired Multi-Timescale Reservoir Computing with Separable Rotation and Dissipation

arXiv:2608.04028v1 Announce Type: cross Abstract: Echo-state networks enable efficient temporal learning by fixing the recurrent dynamics and training only a linear readout. However, conventional rese

Link prediction on multi-relational graphs from an influence propagation perspective

arXiv:2608.05016v1 Announce Type: cross Abstract: Predicting the existence and type of links (edges) between nodes in a multi-relational graph is key for applications from social interaction predictio

local-aiarxiv-cs-lg

LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content

model-releasesarxiv-cs-cv

arXiv:2410.10783v4 Announce Type: replace Abstract: The large-scale training of multi-modal models on data scraped from the web has shown outstanding utility in infusing these models with the required

LLM-based Vulnerability Discovery in Business Process Documentation

arXiv:2608.04271v1 Announce Type: cross Abstract: Just like software and hardware, business processes are susceptible to vulnerabilities that can lead to product quality issues, delays, and increased

researcharxiv-cs-cl

LLMs Struggle to Measure What Distinguishes Students of Different Proficiency Levels: A Study of Item Discrimination in Reading Comprehension Assessment

arXiv:2606.18709v2 Announce Type: replace Abstract: Existing work on LLM-based educational assessment has focused largely on item difficulty, but difficulty alone does not indicate whether an item mea

safetyarxiv-cs-cl

Local Violation Certification for Linear Predict-Then-Optimize Pipelines

arXiv:2608.04474v1 Announce Type: new Abstract: Data-driven decision pipelines combining predictive machine learning models with downstream optimization software are increasingly used to make high-sta

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions

arXiv:2608.02491v2 Announce Type: replace Abstract: Language models have taken on the role of a very new type of technology, by virtue of their 'human-ness' and rapid integration into users' daily liv

safetyarxiv-cs-ai

Looking in the Mirror: Introspecting Side-Effect Misalignments Induced by Fine-Tuning

arXiv:2608.04347v1 Announce Type: new Abstract: Fine-tuning enables a source model to acquire desired capabilities and behaviors in a target domain while retaining much of its general-purpose competen

LoRetta: A Foundation Model and Extensive Dataset for Global-Scale Remote Sensing Dense Image Matching

model-releasesarxiv-cs-cv

arXiv:2608.04106v1 Announce Type: new Abstract: Dense image matching establishes pixel-wise correspondences and underpins broad applications in computer vision and photogrammetry. However, extending d

MALT: Lightweight Curvature-Aware Muon via Diagonal Preconditioning

arXiv:2608.05088v1 Announce Type: new Abstract: Muon has recently emerged as a promising alternative to AdamW for language model pretraining by orthogonalizing momentum matrices using Newton-Schulz it

researcharxiv-cs-lg

Mamba with Hierarchical Memory: Solving Representation Bottleneck in Long Sequence Modeling

arXiv:2608.02347v2 Announce Type: replace Abstract: Recurrent linear attention models (RLAs) such as Mamba offer efficient linear-time sequence modeling as an alternative to Transformers, yet their fi

Manipulation-Proof Oblivious Audits against Deceptive Model Providers

arXiv:2608.04365v1 Announce Type: new Abstract: Audits have emerged as a critical instrument for algorithmic governance, providing a mechanism for external scrutiny and governance of machine learning

MarsCast: Transfer Learning of AI Weather Foundation Models to Planetary Atmospheres

arXiv:2608.05054v1 Announce Type: cross Abstract: We investigate the transferability of Earth weather foundation models to planetary atmospheres by adapting the GraphCast graph neural weather forecast

Masked diffusion enables coherent beat tracking

arXiv:2608.04624v1 Announce Type: cross Abstract: Current neural networks for beat tracking generate invalid outputs, such as consecutive downbeats and erratic tempo changes, even when these are not p

MathDebugger: Detecting and Diagnosing Errors in Synthetic Mathematical Data

arXiv:2502.19058v2 Announce Type: replace Abstract: Synthetic mathematical data has become an important resource for scaling the reasoning capabilities of large language models, yet errors in generate