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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

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

DGX agent

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

13 May 2026

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,

safetyarxiv-cs-lg

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

safetyarxiv-cs-cv

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

safetyarxiv-cs-lg

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.

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

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

safetyarxiv-cs-cv

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

safetyarxiv-cs-lg

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

safetyarxiv-cs-cv

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

Agents

Great example of why you should 1. Run your agent on a separate machine from the sandbox it uses (e.g. sandbox as a tool) 2. Never set env v…

Great example of why you should 1. Run your agent on a separate machine from the sandbox it uses (e.g. sandbox as a tool) 2. Never set env vars in your sandbox. Instead, use something like LangSmith’s

agentsharrison-chase--x

Grid Games: The Power of Multiple Grids for Quantizing Large Language Models

arXiv:2605.12327v1 Announce Type: new Abstract: A major recent advance in quantization is given by microscaled 4-bit formats such as NVFP4 and MXFP4, quantizing values into small groups sharing a scal

GridSFM: A new, small foundation model for the electric grid

tutorialsmicrosoft-research

Introducing GridSFM, a small foundation model that can predict AC optimal power flow in milliseconds, boosting efficiency and unlocking cost savings. Learn how GridSFM gives grid operators direct visi

Grok 4.3 is better than people think.

Elon Musk posted on X claiming that Grok 4.3 performs better than public perception suggests, though the specific performance improvements or capabilities are not detailed in the title. This statement

industryelon-musk--x

Grokking or Glitching? How Low-Precision Drives Slingshot Loss Spikes

arXiv:2605.06152v2 Announce Type: replace-cross Abstract: Deep neural networks exhibit periodic loss spikes during unregularized long-term training, a phenomenon known as the 'Slingshot Mechanism.' Ex

Local Ai

Grounding by Remembering: Cross-Scene and In-Scene Memory for 3D Functional Affordances

arXiv:2605.11616v1 Announce Type: new Abstract: Functional affordance grounding requires more than recognizing an object: an agent must localize the specific region that supports an interaction, such

local-aiarxiv-cs-cv

GRP: Goal-Reversed Prompting for Zero-Shot Evaluation with LLMs

arXiv:2503.06139v2 Announce Type: replace Abstract: Pairwise LLM-as-a-judge evaluation asks the judge to identify the better of two candidate answers. We study a one-line modification that asks for th

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization

arXiv:2605.12369v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models aim for general robot learning by aligning action as a modality within powerful Vision-Language Models (VLMs). Exist

tutorialsarxiv-cs-ro

gym-invmgmt: An Open Benchmarking Framework for Inventory Management Methods

arXiv:2605.11355v1 Announce Type: new Abstract: Inventory-policy comparisons are often difficult to interpret because performance depends on the evaluation contract as much as on the policy itself. Di

h-control: Training-Free Camera Control via Block-Conditional Gibbs Refinement

arXiv:2605.11871v1 Announce Type: new Abstract: Training-free camera control for pretrained flow-matching video generators is a partial-observation inverse problem: a depth-warped guidance video suppl

H2G: Hierarchy-Aware Hyperbolic Grouping for 3D Scenes

arXiv:2605.11967v1 Announce Type: new Abstract: Hierarchical 3D grouping aims to recover scene groups across multiple granularities, from fine object parts to complete objects, without relying on sema

Local Ai

H3D-MarNet: Wavelet-Guided Dual-Path Learning for Metal Artifact Suppression and CT Modality Transformation for Radiotherapy Workflows

arXiv:2605.12252v1 Announce Type: new Abstract: Metal artifacts in computed tomography (CT) severely degrade image quality, compromising diagnostic accuracy and radiotherapy planning, especially in ca

local-aiarxiv-cs-cv

Applications

HamBR: Active Decision Boundary Restoration Based on Hamiltonian Dynamics for Learning with Noisy Labels

arXiv:2605.11383v1 Announce Type: new Abstract: In large-scale visual recognition and data mining tasks, the presence of noisy labels severely undermines the generalization capability of deep neural n

applicationsarxiv-cs-cv

Agents

Has been a blast shipping Engine!! We built engine to automate the agent development loop, and make agents that improve autonomously. Absolu…

Has been a blast shipping Engine!! We built engine to automate the agent development loop, and make agents that improve autonomously. Absolutely cracked team shipping at light speed to create the futu

agentsharrison-chase--x

HE-SNR: Uncovering Latent Logic via Entropy for Guiding Mid-Training on SWE-bench

arXiv:2601.20255v2 Announce Type: replace-cross Abstract: SWE-bench has emerged as the premier benchmark for evaluating Large Language Models on complex software engineering tasks. While these capabil