All entries

FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning

arXiv:2511.14715v3 Announce Type: replace Abstract: Federated learning (FL) enables collaborative model training while preserving data privacy. However, it remains vulnerable to malicious clients who

Local Ai

FlowLPS: Langevin-Proximal Sampling for Flow-based Inverse Problem Solvers

DGX agent

arXiv:2512.07150v2 Announce Type: replace-cross Abstract: Deep generative models are powerful priors for imaging inverse problems, but training-free solvers for latent flow models face a practical fin

local-aiarxiv-cs-cv

13 May 2026

Focusable Monocular Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2605.11756v1 Announce Type: new Abstract: Monocular depth foundation models generalize well across scenes, yet they are typically optimized with uniform pixel-wise objectives that do not disting

Agents

Focusing Influence Mechanism for Multi-Agent Reinforcement Learning

arXiv:2506.19417v2 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) under sparse rewards remains fundamentally challenging because agents often fail to concentrat

agentsarxiv-cs-lg

Local Ai

For more details: https://docs.comfy.org/interface/app-mode

ComfyUI's app mode is a feature that provides an alternative interface for the application, likely offering a simplified or specialized user experience compared to the standard interface. This documen

local-aicomfyui--x

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

arXiv:2605.11048v1 Announce Type: new Abstract: Existing imitation learning methods enable robots to interact autonomously with the physical environment. However, contact-rich manipulation tasks remai

safetyarxiv-cs-ro

Agents

Forecast-aware Gaussian Splatting for Predictive 3D Representation in Language-Guided Pick-and-Place Manipulation

arXiv:2605.11144v1 Announce Type: new Abstract: We introduce Forecast-aware Gaussian Splatting (Forecast-GS), a predictive 3D representation framework for language-conditioned robotic manipulation. Wh

agentsarxiv-cs-ro

Applications

Fractal Graph Contrastive Learning

arXiv:2505.11356v4 Announce Type: replace Abstract: Graph Contrastive Learning (GCL) relies on semantically consistent graph augmentations, but common local perturbations provide limited control over

applicationsarxiv-cs-lg

Freeze Deep, Train Shallow: Interpretable Layer Allocation for Continued Pre-Training

arXiv:2605.11416v1 Announce Type: new Abstract: Selective layer-wise updates are essential for low-cost continued pre-training of Large Language Models (LLMs), yet determining which layers to freeze o

Applications

From a robot expert https://x.com/mattbeane/status/2054667222040330265?s=20

applicationsethan-mollick--x

From a robot expert https://x.com/mattbeane/status/2054667222040330265?s=20 @emollick It is very impressive. Deformable goods? Reflection issues? Imperfect labels? Impossible problems just a few years

From Generic Correlation to Input-Specific Credit in On-Policy Self Distillation

arXiv:2605.11613v1 Announce Type: new Abstract: On-policy self-distillation has emerged as a promising paradigm for post-training language models, in which the model conditions on environment feedback

Local Ai

From Image Hashing to Scene Change Detection

arXiv:2605.12259v1 Announce Type: new Abstract: Image hashing provides compact representations for efficient storage and retrieval but is inherently limited to global comparison and cannot reason abou

local-aiarxiv-cs-cv

From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation

arXiv:2605.12167v1 Announce Type: cross Abstract: Video generation models offer a promising imagination mechanism for robot manipulation by predicting long-horizon future observations, but effectively

From Message-Passing to Linearized Graph Sequence Models

arXiv:2605.12358v1 Announce Type: new Abstract: Message-passing based approaches form the default backbone of most learning architectures on graph-structured data. However, the rapid progress of moder

From Model Uncertainty to Human Attention: Localization-Aware Visual Cues for Scalable Annotation Review

arXiv:2605.12303v1 Announce Type: cross Abstract: High-quality labeled data is essential for training robust machine learning models, yet obtaining annotations at scale remains expensive. AI-assisted

Tutorials

From Observations to States: Latent Time Series Forecasting

arXiv:2602.00297v2 Announce Type: replace Abstract: Deep learning has achieved strong performance in Time Series Forecasting (TSF). However, we identify a critical representation paradox, termed Laten

tutorialsarxiv-cs-lg

Tutorials

From Per-Image Low-Rank to Encoding Mismatch: Rethinking Feature Distillation in Vision Transformers

arXiv:2511.15572v2 Announce Type: replace Abstract: Feature-map knowledge distillation (KD) transfers internal representations well between comparably sized Vision Transformers (ViTs), but it often fa

tutorialsarxiv-cs-cv

From raw data to neutrino candidates: a neural-network pipeline for Baikal-GVD

arXiv:2605.11176v1 Announce Type: cross Abstract: We present a neural-network-based data processing pipeline for Baikal-GVD, designed to improve event reconstruction quality and accelerate neutrino ca

researcharxiv-cs-lg

Agents

From Reaction to Anticipation: Proactive Failure Recovery through Agentic Task Graph for Robotic Manipulation

arXiv:2605.11951v1 Announce Type: new Abstract: Although robotic manipulation has made significant progress, reliable execution remains challenging because task failures are inevitable in dynamic and

agentsarxiv-cs-ro

Applications

From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction

arXiv:2605.11774v1 Announce Type: new Abstract: By processing electronic health records (EHRs) as natural language sequences, large language models (LLMs) have shown potential in clinical prediction t

applicationsarxiv-cs-cl

From Web to Pixels: Bringing Agentic Search into Visual Perception

model-releasesarxiv-cs-cv

arXiv:2605.12497v1 Announce Type: new Abstract: Visual perception connects high-level semantic understanding to pixel-level perception, but most existing settings assume that the decisive evidence for

Fully AI-Generated Image Detection: Definition, Recent Advances and Challenges

arXiv:2502.19716v2 Announce Type: replace Abstract: Recent advances in visual generative models have enabled the creation of highly realistic, fully AI-generated images without relying on real source

Fused Gromov-Wasserstein Distance with Feature Selection

arXiv:2605.12161v1 Announce Type: new Abstract: Fused Gromov-Wasserstein (FGW) distances provide a principled framework for comparing objects by jointly aligning structure and node features. However,

FuTCR: Future-Targeted Contrast and Repulsion for Continual Panoptic Segmentation

arXiv:2605.12451v1 Announce Type: new Abstract: Continual Panoptic Segmentation (CPS) requires methods that can quickly adapt to new categories over time. The nature of this dense prediction task mean

G^2TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models

arXiv:2605.12309v1 Announce Type: new Abstract: The development of separate-encoder Unified multimodal models (UMMs) comes with a rapidly growing inference cost due to dense visual token processing. I

GaitProtector: Impersonation-Driven Gait De-Identification via Training-Free Diffusion Latent Optimization

arXiv:2605.12431v1 Announce Type: new Abstract: Conventional gait de-identification methods often encounter an inherent trade-off: they either provide insufficient identity suppression or introduce sp

GATA2Floor: Graph attention for floor counting in street-view facades

arXiv:2605.11863v1 Announce Type: new Abstract: Automated analysis of building facades from street-level imagery has great potential for urban analytics, energy assessment, and emergency planning. How

GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation

arXiv:2605.11853v1 Announce Type: cross Abstract: Reinforcement learning has become a widely used post-training approach for LLM agents, where training commonly relies on outcome-level rewards that pr

safetyarxiv-cs-cl

Generative AI for Visualizing Highway Construction Hazards Through Synthetic Images and Temporal Sequences

arXiv:2605.11276v1 Announce Type: new Abstract: Highway construction workers face a high risk of serious injury or death. Image-based training materials depicting hazardous scenarios are essential for

Generative AI has not made the world a better place.

Generative AI has not made the world a better place. Since 1893, Princeton professors have left the room when students take their final exams. The idea was that if you treat students honorably, they w

safetygary-marcus--x

Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependencies

arXiv:2605.11531v1 Announce Type: cross Abstract: Physics-based climate projections using general circulation models are essential for assessing future risks, but their coarse resolution limits region

Generative Diffusion Prior Distillation for Long-Context Knowledge Transfer

arXiv:2605.11414v1 Announce Type: new Abstract: While traditional time-series classifiers assume full sequences at inference, practical constraints (latency and cost) often limit inputs to partial pre

GeneZip: Region-Aware Compression for Long Context DNA Modeling

arXiv:2602.17739v3 Announce Type: replace-cross Abstract: Long-context DNA models are limited by token-mixing cost and by how compression allocates representational budget across the genome. Existing

Geometric Factual Recall in Transformers

arXiv:2605.12426v1 Announce Type: new Abstract: How do transformer language models memorize factual associations? A common view casts internal weight matrices as associative memories over pairs of emb

GeomHerd: A Forward-looking Herding Quantification via Ricci Flow Geometry on Agent Interactive Simulations

arXiv:2605.11645v1 Announce Type: cross Abstract: Herding -- where agents align their behaviors and act collectively -- is a central driver of market fragility and systemic risk. Existing approaches t

GeoQuery: Geometry-Query Diffusion for Sparse-View Reconstruction

arXiv:2605.12399v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a prominent paradigm for 3D reconstruction and novel view synthesis. However, it remains vulnerable to sever

GeoR-Bench: Evaluating Geoscience Visual Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.11541v1 Announce Type: new Abstract: Geoscience intelligence is expected to understand, reason about, and predict earth system changes to support human decision-making in critical domains s

GKnow: Measuring the Entanglement of Gender Bias and Factual Gender

arXiv:2605.12299v1 Announce Type: new Abstract: Recent works have analyzed the impact of individual components of neural networks on gendered predictions, often with a focus on mitigating gender bias.

Industry

Good catch @theojaffee 😂

Good catch @theojaffee 😂 Media We asked the CEO of HuggingFace @ClementDelangue what the risks of releasing powerful open source models are. He says restricting AI creates more risk than openness. 'Si

industryclem-delangue--x

Google Named a Leader in the Gartner® Magic Quadrant™ for AI Application Development Platforms: Mid-cycle update

model-releasesgoogle-cloud-ai

May 2026 update: We’ve refreshed this post to reflect our mid-cycle positioning and the evolution of our platform since the report was first published last November. Last fall, Google was recognized a

Industry

Google says Chromebooks will get support through their 'existing date commitment', and 'many' models are 'eligible to transition' to the Googlebook experience (Ben Schoon/9to5Google)

Ben Schoon / 9to5Google: Google says Chromebooks will get support through their “existing date commitment”, and “many” models are “eligible to transition” to the Googlebook experience — During The And

industrytechmeme

Gradient-Boosted Decision Tree for Listwise Context Model in Multimodal Review Helpfulness Prediction

arXiv:2305.12678v3 Announce Type: replace Abstract: Multimodal Review Helpfulness Prediction (MRHP) aims to rank product reviews based on predicted helpfulness scores and has been widely applied in e-

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters

arXiv:2605.11838v1 Announce Type: new Abstract: Gradient clipping is a standard safeguard for training neural networks under noisy, heavy-tailed stochastic gradients; yet, most clipping rules treat al

researcharxiv-cs-lg

Gradient-Free Noise Optimization for Reward Alignment in Generative Models

arXiv:2605.11347v1 Announce Type: cross Abstract: Existing reward alignment methods for diffusion and flow models rely on multi-step stochastic trajectories, making them difficult to extend to determi

GRAFT-ATHENA: Self-Improving Agentic Teams for Autonomous Discovery and Evolutionary Numerical Algorithms

arXiv:2605.11117v1 Announce Type: new Abstract: Scientific discovery can be modeled as a sequence of probabilistic decisions that map physical problems to numerical solutions. Recent agentic AI system

GRAFT: Graph-Tokenized LLMs for Tool Planning

arXiv:2605.11706v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to complete complex tasks by selecting and coordinating external tools across multiple steps. This re

GRASP: Guided Residual Adapters with Sample-wise Partitioning

arXiv:2512.01675v2 Announce Type: replace Abstract: Text-to-image flow matching transformers degrade sharply in long-tail settings: tail-class outputs collapse in fidelity and diversity, limiting thei

Industry

Gravitational lens shows a galaxy just 800 million years post-Big Bang

The James Webb Space Telescope observed LAP1-B, an ultra-faint galaxy at 800 million years after the Big Bang, magnified by gravitational lensing from galaxy cluster MACS J0416. LAP1-B is the most che

industryars-technica