Search: “models”

NetDiff: Graph Diffusion with Improved Global Capabilities to Generate and Update Mobile Network Topologies

arXiv:2410.08238v2 Announce Type: replace-cross Abstract: We introduce NetDiff, a node-conditioned denoising diffusion model that generates directional link topologies and a two-slot transmit/receive

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Model Releases

New York Smells: A Large Multimodal Dataset for Olfaction

DGX agent

arXiv:2511.20544v2 Announce Type: replace Abstract: While olfaction is central to how animals perceive the world, this rich chemical sensory modality remains largely inaccessible to machines. One key

model-releasesarxiv-cs-cv

4 Aug 2026

Not All EEG Moments Are Equal: Position-Adaptive Time Scheduling for EEG Generation

arXiv:2608.00048v1 Announce Type: cross Abstract: Electroencephalography (EEG) generation is essential for alleviating data scarcity and enabling large scale neural modeling in brain computer interfac

safetyarxiv-cs-lg

One QK Channel, Many Sources: Guarding Low-Precision Attention Collapse

arXiv:2608.02091v1 Announce Type: new Abstract: A bfloat16 transformer can train normally for many steps and then collapse abruptly. Distinct low-precision errors can trigger the same failure, leaving

Optimizing Minimax Regret in Uncertain MDPs with Small Sets of Policies

arXiv:2608.02509v1 Announce Type: cross Abstract: Sequential decision-making in real-world applications often involves uncertainty about the environment's model. Uncertain Markov decision processes (U

safetyarxiv-cs-lg

Parameter-Dynamic Adaptive Fusion and Calibration Network for RGBT Tracking

arXiv:2608.01807v1 Announce Type: new Abstract: Existing RGBT trackers typically employ fusion functions with fixed parameters across different targets and scenarios. Although dynamic-architecture met

Pixel Ignores, Superpixel Sees: Adverse Weather Image Restoration via Semantic-Center SSM

arXiv:2608.01760v1 Announce Type: new Abstract: Adverse weather image restoration aims to recover clear visibility from degraded images in complex weather conditions. Existing works attempt to address

Tutorials

PixVL: Self-Supervised Training of Pixel-Level MLLMs via a Unified Mask--Text Consistency Cycle

arXiv:2608.01354v1 Announce Type: new Abstract: Recent studies develop pixel-level multimodal large language models (MLLMs) that support both Region Segmentation and Region Understanding, extending mu

tutorialsarxiv-cs-cv

Applications

PyDPF: A Python Package for Differentiable Particle Filtering

arXiv:2510.25693v3 Announce Type: replace-cross Abstract: State-space models (SSMs) are a widely used tool in time series analysis. In the complex systems that arise from real-world data, it is common

applicationsarxiv-cs-lg

Applications

Reassessing the Feasibility of PPG-Based Non-Invasive Blood Glucose Level Estimation

arXiv:2608.01820v1 Announce Type: cross Abstract: Non-invasive blood glucose level (BGL) estimation from photoplethysmography (PPG) holds great promise for wearable health monitoring, but results acro

applicationsarxiv-cs-lg

Recompute or Reuse? Diagnosing and Mitigating Textual Shortcuts in VLM Self-Reflection

arXiv:2608.01930v1 Announce Type: new Abstract: Vision-language models (VLMs) are expected to revise their reasoning when visual evidence changes. Failures to do so are often attributed to insufficien

Relative Parameter Importance in Task-Agnostic Replay-Free Continual Learning

arXiv:2608.00630v1 Announce Type: new Abstract: Achieving continual learning (CL) with deep neural networks requires balancing stability and plasticity while enabling knowledge transfer. In this work,

Local Ai

RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings

arXiv:2608.01311v1 Announce Type: new Abstract: Generating long-form content from extensive internal reports remains challenging for organizations operating under strict privacy and security constrain

local-aiarxiv-cs-cl

RIT*: Riemannian Informed Trees for Cost-Adaptive Optimal Motion Planning

model-releasesarxiv-cs-ro

arXiv:2608.00822v1 Announce Type: new Abstract: We present Riemannian Informed Trees (RIT*), a planning framework that replaces Euclidean primitives in batch-informed search with their Riemannian coun

RMSWeb: Reflection, Failure-Mode Mining, and Salvage-DS for Web Agent Reinforcement Learning

arXiv:2608.00335v1 Announce Type: cross Abstract: Compact web agents can reduce deployment cost, but training them poses challenges in both data collection and post-SFT reinforcement learning (RL). Su

safetyarxiv-cs-cl

Agents

RubricReviewer: From Direct Critique to Objective and Comprehensive Rubric-Driven Peer Review

arXiv:2608.00005v1 Announce Type: new Abstract: Peer review at major venues is under unprecedented submission pressure, motivating the use of large language models (LLMs) as review assistants. Existin

agentsarxiv-cs-cl

SCOPE: Entanglement Frontier Escape for Source-Free Class Unlearning

arXiv:2608.02058v1 Announce Type: new Abstract: Source-free class unlearning erases whole classes using only the forget data, judged at the representation level, where features can leak a class the he

SecondOpinion: Anatomy-Aware Gated Reasoning for Efficient Medical Image Analysis

arXiv:2608.01808v1 Announce Type: new Abstract: Deep learning models for medical image analysis typically apply a fixed amount of computation to every input, regardless of case difficulty. Anatomy-gui

SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning

model-releasesarxiv-cs-cl

arXiv:2608.00485v1 Announce Type: new Abstract: Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods u

Sheaf-theoretic Signal Processing on Graphs: Spectral Theory, Filtering, and Sampling

arXiv:2608.01318v1 Announce Type: cross Abstract: Modern sensing, communication, and learning systems generate heterogeneous network signals, with local data differing in dimension, modality, and geom

SIGMA: Semantic Identifier Grouping for Molecular Autoregression

arXiv:2603.25062v2 Announce Type: replace Abstract: Autoregressive molecular models assign probability to molecular serializations even though chemical identity is invariant to serialization. Equivale

safetyarxiv-cs-lg

Similarity Weighted Aggregation with Global Differential Privacy for Federated Brain Lesion Segmentation

arXiv:2608.00872v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative training of machine learning models across multiple institutions without sharing sensitive data, making

SIPTraj: Map-Free End-to-End Trajectory Prediction via Physics-Guided Scene Interaction

model-releasesarxiv-cs-ro

arXiv:2608.00779v1 Announce Type: new Abstract: Trajectory prediction of surrounding agents is a prerequisite for safe planning and decision making in autonomous driving. Without high-definition (HD)

SoniSpeech: A Large-Scale Open-Vocabulary Tri-Modal Dataset for Wearable Silent Speech Interfaces

arXiv:2608.00803v1 Announce Type: cross Abstract: Wearable silent speech interfaces (SSIs) are limited to small, closed vocabularies. Approaches achieving larger vocabularies require obtrusive hardwar

Staged Multi-Agent Training (SMAT) for Hip Exoskeletons: Metabolic and Biomechanical Validation of a Simulation-Trained Co-Adaptive Controller

arXiv:2608.00715v1 Announce Type: cross Abstract: Learning-based controllers can deliver exoskeleton assistance after training entirely in physics-based simulation, yet few controllers that address hu

Local Ai

SVRepair: Structured Visual Reasoning for Automated Program Repair

arXiv:2602.06090v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently been applied to Automated Program Repair (APR), yet most existing approaches remain unimodal and fa

local-aiarxiv-cs-cv

SyncPlan: Long-Horizon LLM Coordination with Explicit Synchronization and Adaptive Correction

model-releasesarxiv-cs-ro

arXiv:2608.01652v1 Announce Type: new Abstract: LLM-based multi-agent coordination faces a fundamental trade-off between efficiency and adaptivity in dynamic environments. Existing approaches typicall

T^2exture: Sparsely Perturbed Thermal-to-Texture Imaging

arXiv:2608.02192v1 Announce Type: new Abstract: Thermal imaging remains effective under adverse illumination, yet passive long-wave infrared (LWIR) measurements often lack fine texture. Existing therm

The Condition-Number Barrier in Sparse Least Squares

arXiv:2608.02588v1 Announce Type: cross Abstract: In [AS21], Axiotis and Sviridenko conjectured that the linear dependence on the restricted condition number in sparse convex optimization cannot be im

The Elements of Differentiable Programming

arXiv:2403.14606v4 Announce Type: replace Abstract: Artificial intelligence has recently experienced remarkable advances, fueled by large models, vast datasets, accelerated hardware, and, last but not

The Gate, Not the Cache: Gate Provenance Bounds the Closed-Loop Reliability of Training-Free VLA Token Skipping

arXiv:2608.00391v1 Announce Type: new Abstract: Token skipping is a widely used training-free way to accelerate vision--language--action (VLA) models by bypassing computation for most visual tokens at

researcharxiv-cs-ro

The Push-Forward Transform for Continuous and Robust Comparison of Dynamic Shapes

arXiv:2608.02306v1 Announce Type: new Abstract: We introduce a mathematical framework for shape comparison based on mapping functions from the shape domain to a common reference domain. This Push-Forw

Towards Anomaly Detection on Relational Data

arXiv:2606.18621v2 Announce Type: replace Abstract: Relational databases are widely used for managing structured data in real-world systems. Detecting anomalies from such relational data is crucial fo

Training Deep Morphological Neural Networks as Universal Approximators

arXiv:2505.09710v4 Announce Type: replace Abstract: We investigate deep morphological neural networks (DMNNs), studying how changes in algebraic structure affect the expressivity and trainability of d

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes

arXiv:2608.02415v1 Announce Type: new Abstract: Intent classification in Large Language Models (LLMs) involves categorizing user prompts into predefined classes. For instance, given a user prompt, the

researcharxiv-cs-cl

Transformers perform adaptive partial pooling

arXiv:2602.03980v2 Announce Type: replace Abstract: Any language model must decide what to say in novel contexts based on information from similar contexts. But what about contexts that are not novel

researcharxiv-cs-cl

Agents

UEmbed: Unified Sparse and Dense Multimodal Embeddings

arXiv:2608.02583v1 Announce Type: cross Abstract: Sparse retrieval underpins modern search systems, from web search to retrieval-augmented generation. Existing work has introduced Learned Sparse Retri

agentsarxiv-cs-cl

Uncertainty Is Not Enough: Value-of-Information Routing for Mixtures of LoRA Experts

arXiv:2608.02528v1 Announce Type: new Abstract: Mixtures of low-rank adaptation experts increase parameter-efficient capacity by routing each input through a subset of adapters. Recent dynamic routers

Tutorials

UniqueSplat: View-conditioned 3D Gaussian Splatting for Generalizable 3D Reconstruction

arXiv:2608.02145v1 Announce Type: new Abstract: In this paper, we propose UniqueSplat, a view-conditioned feed-forward 3D Gaussian Splatting model to reconstruct customized 3D radiance fields for each

tutorialsarxiv-cs-cv

Unpacking Hateful Memes: Presupposed Context and False Claims

arXiv:2510.09935v2 Announce Type: replace Abstract: While memes are often humorous, they are frequently used to disseminate hate, causing serious harm to individuals and society. Current approaches to

researcharxiv-cs-cl

USP-Mamba: Unmixing-Derived Spectral and Structural Prompting for Hyperspectral Image Super-Resolution

arXiv:2608.02401v1 Announce Type: new Abstract: Hyperspectral image super-resolution aims to reconstruct high-resolution imagery while preserving dense spectral information. Recently, Mamba-based mode

safetyarxiv-cs-cv

Volcanic Clouds Detection through QCNN and Geostationary Satellite Multispectral Imagery

arXiv:2608.00072v1 Announce Type: new Abstract: Recent advances in quantum computing are opening new possibilities for Earth Observation (EO) data analysis. Quantum machine learning (QML) approaches o

safetyarxiv-cs-cv

VR3D: View-Robust 3D Representation Learning for Aerial-Ground Person Re-Identification

arXiv:2608.02598v1 Announce Type: new Abstract: Aerial-ground person re-identification is a challenging task due to cross-platform viewpoint variations, which cause severe occlusion and geometric defo

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills

arXiv:2608.01851v1 Announce Type: new Abstract: Robot learning is splitting into two bets: policies that bake competence into frozen weights (vision-language-action, or VLA, models), and agents that w

safetyarxiv-cs-ro

When Do Surrogate Updates Improve Decisions? A Local Theory of Trajectory-Wise Transfer

arXiv:2608.01130v1 Announce Type: new Abstract: A broad range of models face the mismatch where they are updated through trajectory losses but are evaluated by downstream task reward. Here, a trajecto

A Benchmark for Strategic Auditee Gaming Under Continuous Compliance Monitoring

arXiv:2605.06340v2 Announce Type: replace-cross Abstract: Continuous post-deployment compliance audits, mandated by emerging regulations such as the EU AI Act and Digital Services Act, create a class

3 Aug 2026

A robust association between LLM use and scientific productivity: Assessing stopping-time selection

model-releasesarxiv-cs-ai

arXiv:2607.28968v1 Announce Type: cross Abstract: Renault, Bergeaud, and Bosquet (hereafter RBB) argue that dating LLM adoption as the first month in which an author's abstract is flagged induces a st

3 Aug 2026

AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers