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I shipped an offline SD app for Android. It's slow, your phone will get warm, and it's completely free.

local-air-stablediffusion

I need to check the actual content of this post to provide an accurate summary. A developer released a free, offline Stable Diffusion application for Android that enables local image generation withou

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Applications

I think frontier model writing is good! It often has a sense of style & tone, variations in sentence structure & length, some great phrasing…

DGX agent

I think frontier model writing is good! It often has a sense of style & tone, variations in sentence structure & length, some great phrasing, etc But it also has some weak spots (fiction!) & clear tic

applicationsethan-mollick--x

12 May 2026

Applications

IBM’s enterprise AI strategy makes trust and control the production test

Before artificial intelligence can scale, governed enterprise AI has to prove it can be trusted. As companies move from pilots to production, the real test is whether platforms can bring automation, t

applicationssiliconangle

ICT-NLP at SemEval-2026 Task 3: Less Is More -- Multilingual Encoder with Joint Training and Adaptive Ensemble for Dimensional Aspect Sentiment Regression

arXiv:2605.10560v1 Announce Type: new Abstract: This paper describes our system to SemEval-2026 Task 3 Track A Subtask 1 on Dimensional Aspect Sentiment Regression (DimASR). We propose a lightweight a

researcharxiv-cs-cl

Identified-Set Geometry of Distributional Model Extraction under Top-K Censored API Access

arXiv:2605.10407v1 Announce Type: new Abstract: Modern LLM APIs often reveal only top-K logit scores and censor the remaining vocabulary. We study the per-position distribution-recovery limits of this

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics

arXiv:2403.18136v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have gained popularity in numerous domains, yet they are vulnerable to backdoor attacks that can compromise their

Identifying Multi-Hit Cancer Drivers Without Massive Parallelization: A CP, MIP, and Column Generation Framework

model-releasesarxiv-cs-lg

arXiv:2602.22551v2 Announce Type: replace-cross Abstract: Cancer is often driven by specific combinations of an estimated two to nine gene mutations, known as multi-hit combinations. Identifying these

Idira launches as Palo Alto Networks extends CyberArk tech to machine and agentic identities

model-releasessiliconangle

Palo Alto Networks Inc. today launched Idira, a new identity security platform designed to manage human, machine and artificial intelligence agent identities across the enterprise under a single privi

Industry

If you want to get a sense of the AI writing gap, just look at the horrible prompting jobs in the replies. “Write a hot take! In all lowerca…

industryallie-k--miller--x

If you want to get a sense of the AI writing gap, just look at the horrible prompting jobs in the replies. “Write a hot take! In all lowercase! Add an analogy to randomly summarize the tweet - which n

Industry

@iliketeslas I have friends who never touch the wheel anymore because of it

This post likely discusses Tesla's autonomous driving capabilities, specifically how some users have become so reliant on autopilot or full self-driving features that they rarely manually control thei

industryelon-musk--x

Illusion-Aware Visual Preprocessing and Anti-Illusion Prompting for Classic Illusion Understanding in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.08841v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit systematic bias toward visual illusions, recalling memorized facts rather than perceiving actual visual difference

IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization

arXiv:2605.09127v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) has attracted growing attention as a unified framework for planning and control in contact-rich robotic

researcharxiv-cs-ro

Impact of Connectivity on Laplacian Representations in Reinforcement Learning

arXiv:2603.08558v2 Announce Type: replace Abstract: Learning compact state representations in Markov Decision Processes (MDPs) has proven crucial for addressing the curse of dimensionality in large-sc

Implicit Hypothesis Testing and Divergence Preservation in Neural Network Representations

arXiv:2601.20477v3 Announce Type: replace Abstract: We study the training dynamics of neural classifiers through the lens of binary hypothesis testing. We re-formalize classification as a collection o

Improved Mean Flows: On the Challenges of Fastforward Generative Models

arXiv:2512.02012v2 Announce Type: replace Abstract: MeanFlow (MF) has recently been established as a framework for one-step generative modeling. However, its ``fastforward'' nature introduces key chal

Improving Generalization by Permutation Routing Across Model Copies

arXiv:2605.09256v1 Announce Type: cross Abstract: We introduce a use of the (M)-cover (or (M)-layer) transform for machine learning. The method replicates a model (M) times, but instead of coupling th

Tutorials

Improving Generative Adversarial Networks with Self-Distillation

arXiv:2605.08577v1 Announce Type: new Abstract: In modern GANs, maintaining an Exponential Moving Average (EMA) of the generator's weights is a standard practice, as such an averaged model consistentl

tutorialsarxiv-cs-cv

Improving Human Image Animation via Semantic Representation Alignment

arXiv:2605.10523v1 Announce Type: new Abstract: The field of image-to-video generation has made remarkable progress. However, challenges such as human limb twisting and facial distortion persist, espe

safetyarxiv-cs-cv

Improving Lexical Difficulty Prediction with Context-Aligned Contrastive Learning and Ridge Ensembling

arXiv:2605.08950v1 Announce Type: cross Abstract: Lexical difficulty prediction is a fundamental problem in language learning and readability assessment, requiring models to estimate word difficulty a

safetyarxiv-cs-ai

Improving Temporal Action Segmentation via Constraint-Aware Decoding

arXiv:2605.10149v1 Announce Type: new Abstract: Temporal action segmentation (TAS) divides untrimmed videos into labeled action segments. While fully supervised methods have advanced the field, challe

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards

arXiv:2603.00918v3 Announce Type: replace-cross Abstract: Text-to-image generation powers content creation across design, media, and data augmentation. Post-training of text-to-image generative models

safetyarxiv-cs-ai

Improving TMS EEG Signal Quality for Closed-Loop Neuro Stimulation via Source-Domain Denoising

arXiv:2605.08184v1 Announce Type: cross Abstract: This research addresses a validated TMS EEG cleaning pipeline and a corresponding benchmark dataset. It evaluates two widely used artifact removal pip

'In California, every professor has 10 different startups with their students. In some Canadian universities, it's one professor out of ten.…

'In California, every professor has 10 different startups with their students. In some Canadian universities, it's one professor out of ten.' @jpineau1, Chief AI Officer at @Cohere at #WebSummitVancou

model-releasescohere--x

In-Context Fixation: When Demonstrated Labels Override Semantics in Few-Shot Classification

arXiv:2605.08295v1 Announce Type: cross Abstract: While random demonstration labels barely hurt in-context learning (Min et al., 2022), we show that homogeneous labels--even semantically valid ones--c

In KAME, a fast speech model starts replying instantly, while a backend LLM runs in parallel to inject deep knowledge on the fly. It’s a com…

In KAME, a fast speech model starts replying instantly, while a backend LLM runs in parallel to inject deep knowledge on the fly. It’s a completely different way to approach conversational AI, making

researchdavid-ha--x

Incorporating rank-free coupling and external field via an incoherent modulated spatial photonic Ising machine

arXiv:2512.21587v2 Announce Type: replace-cross Abstract: Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based sche

Increasing the Efficiency of DETR for Maritime High-Resolution Images

arXiv:2605.10269v1 Announce Type: new Abstract: Maritime object detection is critical for the safe navigation of unmanned surface vessels (USVs), requiring accurate recognition of obstacles from small

Incremental Multilingual Text2Cypher with Adapter Combination

model-releasesarxiv-cs-cl

arXiv:2601.16097v2 Announce Type: replace Abstract: Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, whi

Tutorials

Inductive Entity Representations from Text via Link Prediction

arXiv:2010.03496v4 Announce Type: replace-cross Abstract: Knowledge Graphs (KG) are of vital importance for multiple applications on the web, including information retrieval, recommender systems, and

tutorialsarxiv-cs-ai

IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs

arXiv:2605.10267v1 Announce Type: new Abstract: In industrial procurement, an LLM answer is useful only if it survives a standards check: recommended material must match operating condition, every par

INFANiTE: Implicit Neural representation for high-resolution Fetal brain spatio-temporal Atlas learNing from clinical Thick-slicE MRI

arXiv:2605.09977v1 Announce Type: new Abstract: Spatio-temporal fetal brain atlases are important for characterizing normative neurodevelopment and identifying congenital anomalies. However, existing

Infinite Mask Diffusion for Few-Step Distillation

arXiv:2605.10518v1 Announce Type: cross Abstract: Masked Diffusion Models (MDMs) have emerged as a promising alternative to autoregressive models in language modeling, offering the advantages of paral

researcharxiv-cs-ai

Applications

Information Density as a Quantitative Measure for AI-enabled Virtual Sensing: Feasibility and Limits

arXiv:2605.08180v1 Announce Type: cross Abstract: Modern IoT and sensor networks generate vast amounts of data, posing significant challenges for storage, transmission, and real-time processing. Tradi

applicationsarxiv-cs-ai

Applications

Information Filtering via Variational Regularization for Robot Manipulation

arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,

applicationsarxiv-cs-ro

Agents

Informative Path Planning with Guaranteed Estimation Uncertainty

arXiv:2602.05198v2 Announce Type: replace Abstract: Environmental monitoring robots often need to estimate data fields (e.g., salinity, temperature, bathymetry) under tight resource constraints. Class

agentsarxiv-cs-ro

Initiation of Interaction Detection Framework using a Nonverbal Cue for Human-Robot Interaction

arXiv:2605.10087v1 Announce Type: new Abstract: This paper describes an initiation of interaction(IoI) detection framework without keywords for human-robot interaction(HRI) based on audio and vision s

local-aiarxiv-cs-cv

Inpainting physics: self-supervised learning for context-driven fluid simulation

arXiv:2605.08832v1 Announce Type: new Abstract: Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such

local-aiarxiv-cs-lg

Agents

Insider Attacks in Multi-Agent LLM Consensus Systems

arXiv:2605.08268v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in multi-agent systems where agents communicate in natural language to solve tasks jointly. A k

agentsarxiv-cs-ai

Insight: Enhancing Mobile Accessibility for Blind and Visually Impaired Users with LLMs

arXiv:2605.09803v1 Announce Type: cross Abstract: This research paper addresses the limitations of current mobile accessibility services like TalkBack, which provide manual gesture-based sequential fe

researcharxiv-cs-ai

Instance-Adaptive Online Multicalibration

arXiv:2605.09273v1 Announce Type: new Abstract: We study online multicalibration beyond the worst-case. We give a single, efficient algorithm which dynamically interpolates between benign and worst-ca

Instruction Adherence in Coding Agent Configuration Files: A Factorial Study of Four File-Structure Variables

model-releasesarxiv-cs-cl

arXiv:2605.10039v1 Announce Type: cross Abstract: Frontier coding agents read configuration files (CLAUDE.md, AGENTS.md, Cursor Rules) at session start and are expected to follow the conventions insid

Instruction Anchor: Dissecting the Mechanistic Dynamics of Modality Arbitration

arXiv:2602.03677v2 Announce Type: replace Abstract: Modality following is the ability to selectively leverage multimodal contexts based on user instructions. It is fundamental to the safety and reliab

safetyarxiv-cs-cl

Industry

Instructure reached a deal with hackers who breached its Canvas platform to return stolen data and destroy copies, without disclosing what it gave in exchange (Qasim Nauman/New York Times)

Qasim Nauman / New York Times: Instructure reached a deal with hackers who breached its Canvas platform to return stolen data and destroy copies, without disclosing what it gave in exchange — Instruct

industrytechmeme

Integrated Hierarchical Decision-Making in Inverse Kinematic Planning and Control

arXiv:2412.01324v4 Announce Type: replace Abstract: This work presents a novel and efficient nonlinear programming framework that tightly integrates hierarchical decision-making with whole-body invers

researcharxiv-cs-ro

Intelligent Autonomous Orchestration for Distributed Cloud Resources using Complex-Stability Analysis

arXiv:2605.08139v1 Announce Type: cross Abstract: In modern distributed cloud environments, efficient resource allocation is required as traditional scaling mechanisms are often subject to cloud thras

safetyarxiv-cs-ai

Tutorials

Interactive Benchmarks

arXiv:2603.04737v2 Announce Type: replace Abstract: Existing reasoning evaluation paradigms suffer from different limitations: fixed benchmarks are increasingly saturated and vulnerable to contaminati

tutorialsarxiv-cs-ai

Interactive Critique-Revision Training for Reliable Structured LLM Generation

arXiv:2605.08327v1 Announce Type: cross Abstract: In structured decision-making workflows such as form filling, compliance checking, and maintenance reporting, LLM outputs must be locally correct, glo

local-aiarxiv-cs-ai

Interactive Inverse Reinforcement Learning of Interaction Scenarios via Bi-level Optimization

arXiv:2605.08131v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) learns a reward function and a corresponding policy that best fit the demonstration data of an expert. However, in

safetyarxiv-cs-lg