Search: “models”

STDA-Net: Spectrogram-Based Domain Adaptation for cross-dataset Sleep Stage Classification

arXiv:2605.06736v1 Announce Type: cross Abstract: Accurate sleep stage classification across datasets remains challenging due to variability in EEG channel montages, sampling rates, recording environm

safetyarxiv-cs-ai

Research

Streaming Adversarial Robustness in Fuzzy ARTMAP: Mechanism-Aligned Evaluation, Progressive Training, and Interpretable Diagnostics

DGX agent

arXiv:2605.06902v1 Announce Type: new Abstract: Adversarial robustness has been studied extensively for offline deep networks, but less is known about strict single-pass streaming neural learners. Thi

researcharxiv-cs-lg

11 May 2026

Structured Role-Aware Policy Optimization for Multimodal Reasoning

arXiv:2605.07274v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR), especially with Group Relative Policy Optimization (GRPO), has shown strong potential for improvi

safetyarxiv-cs-ai

TCMIIES: A Browser-Based LLM-Powered Intelligent Information Extraction System for Academic Literature

arXiv:2605.07507v1 Announce Type: new Abstract: The exponential growth of academic publications has created an urgent need for automated tools capable of extracting structured knowledge from unstructu

local-aiarxiv-cs-cl

// The Memory Curse in LLM Agents // (bookmark it) Long histories apparently degrades agents as they become increasingly history-following a…

// The Memory Curse in LLM Agents // (bookmark it) Long histories apparently degrades agents as they become increasingly history-following and risk-minimizing. Across 7 LLMs and 4 social dilemma games

tutorialsdair-ai--x

Think-with-Rubrics: From External Evaluator to Internal Reasoning Guidance

arXiv:2605.07461v1 Announce Type: new Abstract: Rubrics have been extensively utilized for evaluating unverifiable, open-ended tasks, with recent research incorporating them into reward systems for re

safetyarxiv-cs-cl

Agents

Towards Security-Auditable LLM Agents: A Unified Graph Representation

arXiv:2605.06812v1 Announce Type: new Abstract: LLM-based agentic systems are rapidly evolving to perform complex autonomous tasks through dynamic tool invocation, stateful memory management, and mult

agentsarxiv-cs-ai

Tracing the Arrow of Time: Diagnosing Temporal Information Flow in Video-LLMs

arXiv:2605.07568v1 Announce Type: cross Abstract: The Arrow-of-Time (AoT) task, determining whether a video plays forward or backward by recognizing temporal irreversibility, is one humans solve with

researcharxiv-cs-cl

TraXion: Rethinking Pre-training Frameworks for Mobility and Beyond

arXiv:2605.06906v1 Announce Type: new Abstract: Human mobility differs from text and from generic time series in three structural ways: visits are tuple-valued events whose meaning depends on the join

Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders

arXiv:2605.07922v1 Announce Type: new Abstract: Learning hierarchical features in Sparse Autoencoders (SAEs) is essential for capturing the structured nature of real-world data and mitigating issues l

tutorialsarxiv-cs-lg

Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting

arXiv:2605.06916v1 Announce Type: new Abstract: Probabilistic weather forecasting requires not only accurate trajectories, but calibrated distributions over plausible atmospheric futures. Recent data-

User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums

arXiv:2509.11777v2 Announce Type: replace Abstract: Customer feedback in industrial forums offers rich but underexplored insights into real-world product experience. Yet systematic analysis remains ch

applicationsarxiv-cs-cl

VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagation

arXiv:2508.06819v3 Announce Type: replace Abstract: The task of parsing subcutaneous vessels in clinical images is often hindered by the high cost and limited availability of ground truth data, as wel

Agents

WebClipper: Efficient Evolution of Web Agents with Graph-based Trajectory Pruning

arXiv:2602.12852v2 Announce Type: replace Abstract: Deep Research systems based on web agents have shown strong potential in solving complex information-seeking tasks, yet their search efficiency rema

agentsarxiv-cs-ai

Weblica: Scalable and Reproducible Training Environments for Visual Web Agents

arXiv:2605.06761v1 Announce Type: new Abstract: The web is complex, open-ended, and constantly changing, making it challenging to scale training data for visual web agents. Existing data collection at

applicationsarxiv-cs-ai

Zero-Shot Imagined Speech Decoding via Imagined-to-Listened MEG Mapping

arXiv:2605.08075v1 Announce Type: new Abstract: Decoding imagined speech from non-invasive brain recordings is challenging because imagined datasets are scarce and difficult to align temporally across

safetyarxiv-cs-lg

Artificial Analysis needs to address HiDream-01 Benchmarks

local-air-stablediffusion

HiDream-O1-Image debuted at #8 in the Artificial Analysis Text to Image Arena , and the Reddit post likely discusses whether this benchmark inclusion and ranking adequately reflect HiDream-01's perfor

10 May 2026

Industry

AI Ascent 2026

AI Ascent 2026 is Sequoia Capital's event that convened leading AI researchers and founders including Greg Brockman, Andrej Karpathy, and Demis Hassabis. The event featured discussions on AI agents, s

industrysequoia-capital

I promise this will be the best 20 min you spend today! Robotics: Endgame, the sequel to my last year's Sequoia AI Ascent talk, 'Physical Tu…

I promise this will be the best 20 min you spend today! Robotics: Endgame, the sequel to my last year's Sequoia AI Ascent talk, 'Physical Turing Test'. I laid out the roadmap for solving Physical AGI

local-aijim-fan--x

Agents

Kimi K2.6 on @baseten is ~5x cheaper than Opus 4.7 For a large majority of tasks, it's roughly the same performance If you want to use open …

Kimi K2.6, deployed on Baseten, offers approximately 5x cost savings compared to Claude Opus 4.7 while maintaining comparable performance on most tasks, making it a viable open-source alternative for

agentsharrison-chase--x

The human brain🧠 is incredibly efficient because it only activates the specific neurons needed for a thought. Modern LLMs naturally try to …

The human brain🧠 is incredibly efficient because it only activates the specific neurons needed for a thought. Modern LLMs naturally try to do this too (> 95% of neurons in feedforward layers stay sile

safetydavid-ha--x

3D Printing of Passively Actuated Self-Folding Robots with Integrated Functional Modules

arXiv:2605.04757v1 Announce Type: new Abstract: We introduce an elastic-driven self-folding approach that fabricates robots directly from flat 3D-printed conductive PLA nets. Elastic bands routed thro

researcharxiv-cs-ro

A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning

arXiv:2605.04274v1 Announce Type: new Abstract: Accurate boundary detection in high-dimensional data remains a central challenge in unsupervised learning, particularly in the presence of non-linear st

Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation

arXiv:2504.13614v2 Announce Type: replace-cross Abstract: The rapid growth of the internet has made personalized recommendation systems indispensable. Graph-based sequential recommendation systems, po

tutorialsarxiv-cs-ai

AI4EOSC: a Federated Cloud Platform for Artificial Intelligence in Scientific Research

arXiv:2512.16455v3 Announce Type: replace-cross Abstract: The rapid growth of Artificial Intelligence and Machine Learning in scientific research has highlighted a gap between industry-standard MLOps

applicationsarxiv-cs-ai

Anny-Fit: All-Age Human Mesh Recovery

arXiv:2605.04728v1 Announce Type: new Abstract: Recovering 3D human pose and shape from a single image remains a cornerstone of human-centric vision, yet most methods assume adult subjects and optimiz

Cardiovascular disease classification using radiomics and geometric features from cardiac CT

arXiv:2506.22226v2 Announce Type: replace-cross Abstract: Automatic detection and classification of Cardiovascular disease (CVD) from Computed Tomography (CT) images play an important part in facilita

researcharxiv-cs-cv

CHE-TKG: Collaborative Historical Evidence and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning

arXiv:2605.04652v1 Announce Type: new Abstract: Temporal knowledge graph (TKG) reasoning aims to predict future events from historical facts. A key challenge lies in jointly capturing two sources of p

safetyarxiv-cs-cl

Combining Abstract Argumentation and Machine Learning for Efficiently Analyzing Low-Level Process Event Streams

arXiv:2505.05880v2 Announce Type: replace-cross Abstract: Monitoring and analyzing process traces is a critical task for modern companies and organizations. In scenarios where there is a gap between t

Constraint-Aware Execution Planning for Hybrid Space-Ground Compute Workloads

arXiv:2605.04052v1 Announce Type: cross Abstract: Low Earth orbit (LEO) satellites increasingly carry compute hardware capable of on-board processing, yet each satellite generates roughly two orders o

Covariance-Aware Goodness for Scalable Forward-Forward Learning

arXiv:2605.04346v1 Announce Type: cross Abstract: The Forward-Forward algorithm eliminates global gradient flow and full network activations storage. However, in convolutional settings, existing BP-fr

local-aiarxiv-cs-cv

Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise

arXiv:2408.09929v2 Announce Type: replace-cross Abstract: Inspired by the idea of Positive-incentive Noise (Pi-Noise or pi-Noise) that aims at learning the reliable noise beneficial to tasks, we scien

DeFed-GMM-DaDiL: A Decentralized Federated Framework for Domain Adaptation

arXiv:2605.04324v1 Announce Type: new Abstract: Decentralized multi-source domain adaptation seeks to transfer knowledge from multiple heterogeneous and related source domains to an unlabeled target d

Diffusion-Based Feature Denoising with NNMF for Robust handwritten digit multi-class classification

arXiv:2603.29917v2 Announce Type: replace Abstract: This work presents a robust multi-class classification framework for handwritten digits that combines diffusion-driven feature denoising with a hybr

researcharxiv-cs-cv

Do Multimodal RAG Systems Leak Data? A Comprehensive Evaluation of Membership Inference and Image Caption Retrieval Attacks

arXiv:2601.17644v3 Announce Type: replace-cross Abstract: The growing adoption of multimodal Retrieval-Augmented Generation (mRAG) pipelines for vision-centric tasks (e.g., visual QA) introduces impor

applicationsarxiv-cs-ai

DPD-Cancer: Explainable Graph-Based Deep Learning for Small Molecule Anti-Cancer Activity Prediction

arXiv:2603.26114v2 Announce Type: replace Abstract: DPD-Cancer is a graph-attention deep learning framework for predicting small-molecule DPD-Cancer is a graph-attention deep learning framework for pr

Hardware

DualTCN: A Physics-Constrained Temporal Convolutional Network for 2 Time-Domain Marine CSEM Inversion

arXiv:2605.04997v1 Announce Type: new Abstract: DualTCN is the first deep-learning framework for inverting time-domain marine controlled-source electromagnetic (MCSEM) transient data. Moving away from

hardwarearxiv-cs-lg

Efficient Geometry-Controlled High-Resolution Satellite Image Synthesis

arXiv:2605.04557v1 Announce Type: new Abstract: High-resolution satellite images are often scarce and costly, especially for remote areas or infrequent events. This shortage hampers the development an

safetyarxiv-cs-cv

EP-GRPO: Entropy-Progress Aligned Group Relative Policy Optimization with Implicit Process Guidance

arXiv:2605.04960v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), particularly Group Relative Policy Optimization (GRPO), has advanced LLM reasoning. However, GRPO

safetyarxiv-cs-lg

Estimating the expected output of wide random MLPs more efficiently than sampling

arXiv:2605.05179v1 Announce Type: new Abstract: By far the most common way to estimate an expected loss in machine learning is to draw samples, compute the loss on each one, and take the empirical ave

tutorialsarxiv-cs-lg

Event-Based Early Warning of Vineyard Disease Risk from Environmental Time Series

arXiv:2605.04548v1 Announce Type: new Abstract: Accurate early warning of vineyard disease risk from environmental observations is essential for timely intervention and more sustainable crop protectio

Every Step Counts: Step-Level Credit Assignment for Tool-Integrated Text-to-SQL

arXiv:2605.04719v1 Announce Type: new Abstract: Tool-integrated Text-to-SQL parsing has emerged as a promising paradigm, framing SQL generation as a sequential decision-making process interleaved with

safetyarxiv-cs-cl

Flux.2-Klein Tiling Upscale Workflow

local-air-stablediffusion

A ComfyUI workflow that uses Flux 2 Klein for the first upscale pass where detail is introduced carefully, then uses SeedVR2 to push the final resolution higher via tiling. The workflow maintains the

From Language to Logic: A Theoretical Architecture for VLM-Grounded Safe Navigation

arXiv:2605.04327v1 Announce Type: new Abstract: We propose an architecture for integrating high-level, human-provided safety rules and operator-aligned semantic preferences into autonomous robot navig

safetyarxiv-cs-ro

Fully Guided Neural Schrodinger bridge for Brain MR image synthesis

arXiv:2501.14171v3 Announce Type: replace-cross Abstract: Multi-modal brain MRI provides essential complementary information for clinical diagnosis. However, acquiring all modalities in practice is of

researcharxiv-cs-cv

Gated Multimodal Learning for Interpretable Property Energy Performance Prediction and Retrofit Scenario Analysis

arXiv:2605.05088v1 Announce Type: new Abstract: Achieving resilient and sustainable cities requires scalable approaches to decarbonising residential buildings, which account for about 20% of UK greenh

Gray-Box Poisoning of Continuous Malware Ingestion Pipelines

arXiv:2605.04698v1 Announce Type: cross Abstract: Modern malware detection pipelines rely on continuous data ingestion and machine learning to counter the high volume of novel threats. This work inves

Industry

HF leaderboards are fantastic, thank you @ClementDelangue @Thom_Wolf @NielsRogge for making a critical facet of benchmarks so easy! Check ou…

HF leaderboards are fantastic, thank you @ClementDelangue @Thom_Wolf @NielsRogge for making a critical facet of benchmarks so easy! Check out http://swebench.com as well The SWE-bench Verified leaderb

industryclem-delangue--x