All entries

Enabling self-supervised learned primal dual with Noise2Inverse

arXiv:2606.26991v1 Announce Type: cross Abstract: X-ray computed tomography reconstruction is an ill-posed inverse problem, particularly in low-dose and sparse-angle settings where measurements are no

researcharxiv-cs-lg

Local Ai

EndoUFM: Utilizing Foundation Models for Monocular depth estimation of endoscopic images

DGX agent

arXiv:2508.17916v2 Announce Type: replace Abstract: Depth estimation is a foundational component for 3D reconstruction in minimally invasive endoscopic surgeries. However, existing monocular depth est

local-aiarxiv-cs-cv

26 Jun 2026

EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting

model-releasesarxiv-cs-ai

arXiv:2606.27277v1 Announce Type: new Abstract: Earth Observation (EO) forecasting aims to predict future Earth surface dynamics from satellite observations under changing meteorological conditions. I

Epiphany-Aware KV Cache Eviction Without the Attention Matrix

arXiv:2606.26472v1 Announce Type: cross Abstract: As reasoning models emit chains of thought tens of thousands of tokens long, KV cache increasingly becomes a deployment bottleneck. Existing cache evi

applicationsarxiv-cs-cl

Equivariance and Augmentation for Bayesian Neural Networks

arXiv:2606.26273v1 Announce Type: new Abstract: Symmetries are important for many deep learning tasks, ranging from applications in the sciences to medical imaging. However, there is an ongoing debate

tutorialsarxiv-cs-lg

Erase-then-Delta Attention: Decoupling Erase and Write Addresses in Delta-Rule Linear Attention

arXiv:2606.26560v1 Announce Type: new Abstract: Delta-rule linear attention improves recurrent memory updates by correcting what is already stored at the current write address before writing new conte

researcharxiv-cs-cl

Error-Conditioned Neural Solvers

model-releasesarxiv-cs-ai

arXiv:2606.27354v1 Announce Type: cross Abstract: Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical tas

Escaping Iterative Parameter-Space Noise: Differentially Private Learning with a Hypernetwork

model-releasesarxiv-cs-lg

arXiv:2606.26772v1 Announce Type: new Abstract: Differentially private (DP) training of neural networks is often hindered by the large amount of noise required by gradient-based methods such as DP-SGD

Estimating Orbital Parameters of Direct Imaging Exoplanet Using Neural Network

model-releasesarxiv-cs-lg

arXiv:2510.17459v3 Announce Type: replace-cross Abstract: In this work, we propose a flow-matching Markov chain Monte Carlo (FM-MCMC) algorithm for estimating the orbital parameters of exoplanetary sy

Estimating Uncertainty in Classifier Performance with Applications to Large Language Models and Nested Data

arXiv:2606.26422v1 Announce Type: new Abstract: Researchers increasingly use text classification--supervised models or large language models--to measure constructs from natural language, providing met

Evaluation Pitfalls and Challenges in Multimedia Event Extraction

arXiv:2606.26775v1 Announce Type: new Abstract: Multimedia event extraction aims to jointly identify events and their arguments across multiple modalities, such as text and images, to support more com

applicationsarxiv-cs-cl

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs

arXiv:2606.26492v1 Announce Type: cross Abstract: Deep Learning (DL) programs can fail during training for many reasons, and diagnosing the cause is a costly and time-consuming maintenance task. Techn

applicationsarxiv-cs-ai

Event-Aware Instructed Assistant for Referring Video Segmentation

arXiv:2606.26994v1 Announce Type: cross Abstract: Existing referring video segmentation methods often treat a video as a single event consisting of multiple images, overlooking the fact that a video t

Hardware

Event-based Gaze Control System for Accurate Real-time Spin Estimation in Professional Ball Games

arXiv:2606.26780v1 Announce Type: new Abstract: Spin plays a crucial role in many ball sports due to its effect on the trajectory of the ball. Vision-based estimation of the ball's spin during a game

hardwarearxiv-cs-cv

EvoEmbedding: Evolvable Representations for Long-Context Retrieval and Agentic Memory

arXiv:2606.21649v2 Announce Type: replace Abstract: Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This

agentsarxiv-cs-cl

EVOM: Agentic Meta-Evolution of Actor-Critic Architectures for Reinforcement Learning

arXiv:2606.26327v1 Announce Type: cross Abstract: In actor-critic reinforcement learning, network architectures are typically manually designed. Automating this design is challenging because each cand

safetyarxiv-cs-ai

EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modeling

arXiv:2606.26578v1 Announce Type: new Abstract: Automating optimization modeling from natural language with large language models (LLMs) faces two key challenges. First, training corpora lack structur

agentsarxiv-cs-ai

Exact and Deterministic Patch Descriptor Retrieval via Hierarchical Normalization

arXiv:2606.27280v1 Announce Type: new Abstract: We present a patch descriptor retrieval method that returns the exact nearest neighbour -- provably identical to exhaustive full-vector search -- while

excited to come down to SF for @aidotengineer next week! let’s hang :)

excited to come down to SF for @aidotengineer next week! let’s hang :) We're hosting a BabyAGI x Physical AI Happy Hour with @yoheinakajima on June 30th, 6PM in SF! If you're building across AI agents

agentsyohei-nakajima--x

Excited to see @cohere open-source how they use AI coding agents to maintain their vLLM fork. 🙌 Keeping a long-lived fork in sync is tricky…

Excited to see @cohere open-source how they use AI coding agents to maintain their vLLM fork. 🙌 Keeping a long-lived fork in sync is tricky. Their agent treats it as a control loop: rebase onto each u

agentscohere--x

Explainable Ensemble-Based Machine Learning Models for Detecting the Presence of Cirrhosis in Hepatitis C Patients

arXiv:2606.26561v1 Announce Type: new Abstract: Hepatitis C is a liver infection caused by a virus, which results in mild to severe inflammation of the liver. Over many years, hepatitis C gradually da

Explaining Temporal Graph Neural Networks via Feature-induced Information Flow

arXiv:2606.27201v1 Announce Type: new Abstract: Event-based Temporal Graph Neural Networks (ETGNNs) have demonstrated strong performance across a wide range of applications, including social network a

applicationsarxiv-cs-lg

Exploring the Intrinsic Geometry of Diffusion Models with Constrained Inverse Kinematics

arXiv:2606.26408v1 Announce Type: new Abstract: Recent studies suggest that diffusion models can recover geometric structure in the data manifolds they are trained on, yet the supporting evidence has

researcharxiv-cs-ro

Extracting Neural Materials from Multi-view Images

arXiv:2606.26715v1 Announce Type: new Abstract: Neural materials can represent complex specular reflections and scattering effects in a compact, universal basis. However, acquiring and authoring such

Extracting Problem and Method Sentence from Scientific Papers: A Context-enhanced Transformer Using Formulaic Expression Desensitization

arXiv:2606.26481v1 Announce Type: new Abstract: Billions of scientific papers lead to the need to identify essential parts from the massive text. Scientific research is an activity from putting forwar

tutorialsarxiv-cs-cl

extsc{DiARC}: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models

model-releasesarxiv-cs-ai

arXiv:2606.26530v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC;~itealp{chollet2019measure}) contains tasks that require summarizing patterns from limited grid samples and

Eyes-on-Me: Scalable RAG Poisoning through Transferable Attention-Steering Attractors

arXiv:2510.00586v3 Announce Type: replace-cross Abstract: Existing data poisoning attacks on retrieval-augmented generation (RAG) systems scale poorly because they require costly optimization of poiso

researcharxiv-cs-cl

Fantastic interview: Ed Elson is talking with Gary Marcus about AI tech, overrelience on LLMs, the business of AI, etc. I totally enjoyed th…

Fantastic interview: Ed Elson is talking with Gary Marcus about AI tech, overrelience on LLMs, the business of AI, etc. I totally enjoyed this: https://youtu.be/_pSivPlRx5o?si=dzrJKpUGTHE0Y76I @edels0

safetygary-marcus--x

Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity

model-releasesarxiv-cs-lg

arXiv:2606.27298v1 Announce Type: cross Abstract: We study the fundamental problem of learning a high-dimensional Gaussian truncated to an unknown halfspace. Lee, Mehrotra and Zampetakis (FOCS'24) rec

Local Ai

Fast LeWorldModel

arXiv:2606.26217v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs), including recent LeWorldModel (LeWM), have become a promising foundation for reconstruction-free vis

local-aiarxiv-cs-cv

FBK's Long-form SpeechLLMs for IWSLT 2026 Instruction Following

arXiv:2606.26819v1 Announce Type: new Abstract: This paper describes our submission to the IWSLT 2026 Instruction Following shared task. SpeechLLMs are developed for both short-form and long-form spee

researcharxiv-cs-cl

FC-Vision: Real-Time Visibility-Aware Replanning for Occlusion-Free Aerial Target Structure Scanning in Unknown Environments

model-releasesarxiv-cs-ro

arXiv:2602.13720v2 Announce Type: replace Abstract: Autonomous aerial scanning of target structures is crucial for practical applications, requiring online adaptation to unknown obstacles during fligh

Industry

FCC accused of hiding Chairman Carr's messages with DOGE and Musk

A federal FOIA lawsuit seeks discovery into DOGE's activities inside the FCC, questioning ethics clearances, data access, and withheld communications tied to contract cuts and Musk-linked entities. Th

industryars-technica

Federated Hash Projected Latent Factor Learning

arXiv:2606.26192v1 Announce Type: new Abstract: Hash Learning (HL) is an efficient representation learning approach that maps real-valued data into compact binary representations. Traditional HL metho

applicationsarxiv-cs-lg

Finally, AI finds its ultimate uncontroversial use. A diffusion model trained on burger recipes 'discovers the classic Big Mac without expli…

applicationsethan-mollick--x

Finally, AI finds its ultimate uncontroversial use. A diffusion model trained on burger recipes 'discovers the classic Big Mac without explicit supervision and generates novel burgers optimized for de

Finding Stationary Points by Comparisons

arXiv:2606.27082v1 Announce Type: new Abstract: We study the problem of finding stationary points of non-convex functions when access to the objective is provided only through a comparison oracle that

researcharxiv-cs-lg

Finding the Time to Think: Learning Planning Budgets in Real-Time RL

arXiv:2606.26463v1 Announce Type: new Abstract: Deliberating takes time. In real-time settings, that time is not free. Standard reinforcement learning (RL) sidesteps this as the environment waits inde

safetyarxiv-cs-lg

Fireworks AI is now live on EvoSkill v1.3.0! You can now use @FireworksAI_HQ directly with EvoSkill to run fast inference on open models as …

model-releasesfireworks-ai--x

Fireworks AI is now live on EvoSkill v1.3.0! You can now use @FireworksAI_HQ directly with EvoSkill to run fast inference on open models as both the evolution harness backend and the LLM scorer. Along

FlameVQA: A Physically-Grounded UAV Wildfire VQA Benchmark with Radiometric Thermal Supervision

model-releasesarxiv-cs-cv

arXiv:2606.27128v1 Announce Type: new Abstract: Wildfire monitoring from UAVs requires reliable reasoning over complex aerial scenes, where smoke, scale variation, and occlusions often limit RGB-only

Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE

arXiv:2606.26938v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures have emerged as a powerful paradigm for scaling diffusion models in visual generation. Recent advancements have f

Forecasting With LLMs: Improved Generalization Through Feature Steering

arXiv:2606.27199v1 Announce Type: new Abstract: Successful forecasting involves identifying patterns between historical and future states of the world which generalize to future observations. We apply

safetyarxiv-cs-cl

ForesightSafety-VLA: A Unified Diagnostic Safety Benchmark for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2606.27079v1 Announce Type: new Abstract: In embodied intelligence, safety is a prerequisite for reliable robot deployment in the physical world. Current vision-language-action (VLA) models cont

Forget, Anticipate and Adapt: Test Time Training for Long Videos

arXiv:2606.26515v1 Announce Type: new Abstract: Test Time Training (TTT) is a mechanism in which a model adapts to an incoming test-sample by performing some self-supervised (SSL) task and updating it

tutorialsarxiv-cs-cv

Fortress and Gatekeeper: Theorizing Transitive Trust in Third-Party Cybersecurity Risk Governance

arXiv:2606.26866v1 Announce Type: cross Abstract: Third-party vendors, such as analytics platforms, cloud services, identity providers, and software suppliers, are increasingly embedded in digital ser

Forward Deployed Engineering is the most critical ingredient for Enterprise AI adoption. It’s why the most important companies on the planet…

Forward Deployed Engineering is the most critical ingredient for Enterprise AI adoption. It’s why the most important companies on the planet are investing so heavily into it. That’s why we put togethe

tutorialsswyx--x

FracEvent: Event-Camera Simulation via Fractional-Relaxation Pixel Dynamics

arXiv:2606.26636v1 Announce Type: new Abstract: Event cameras asynchronously report brightness changes with microsecond-level temporal resolution, but real event data remain difficult to collect at sc

From Celebrities to Anyone: Characterizing AI Nudification Content, Technology, and Community Dynamics on 4chan

arXiv:2606.27234v1 Announce Type: cross Abstract: AI nudification uses generative models to create synthetic non-consensual sexually explicit imagery (SNEACI) of real individuals. Prior work has exami

applicationsarxiv-cs-ai

From Clicks to Intent: Cross-Platform Session Embeddings with LLM-Distilled Taxonomy for Financial Services Recommendations

arXiv:2606.26277v1 Announce Type: cross Abstract: Sequential user behavior modeling is widely adopted in industrial recommender systems; however, significant gaps remain in financial services, where p

applicationsarxiv-cs-ai