All entries

MemeLens: Multilingual Multitask VLMs for Memes

arXiv:2601.12539v3 Announce Type: replace-cross Abstract: Memes are a dominant medium for online communication and manipulation because meaning emerges from interactions between embedded text, imagery

MemORAI: Memory Organization and Retrieval via Adaptive Graph Intelligence for LLM Conversational Agents

Content type

All Blog X Post Paper YouTube Reddit GitHub

DGX agent

arXiv:2605.01386v1 Announce Type: new Abstract: Large Language Models (LLMs) lack persistent memory for long-term personalized conversations. Existing graph-based memory systems suffer from informatio

researcharxiv-cs-cl

5 May 2026

MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization

arXiv:2605.01967v1 Announce Type: cross Abstract: Deploying multimodal models in real-world scenarios requires generalization to new environments where recording conditions differ from training, a cha

applicationsarxiv-cs-cv

Mesh Based Simulations with Spatial and Temporal awareness

arXiv:2605.01542v1 Announce Type: new Abstract: Machine Learning surrogates for Computational Fluid Dynamics (CFD), particularly Graph Neural Networks (GNNs) and Transformers, have become a new import

Meta is using AI on Facebook and Instagram to detect under-13 users by analyzing bone structure, height, and visual cues, but says it's 'not facial recognition' (Emma Roth/The Verge)

Emma Roth / The Verge: Meta is using AI on Facebook and Instagram to detect under-13 users by analyzing bone structure, height, and visual cues, but says it's “not facial recognition” — ‘We want to be

industrytechmeme

Meta-learning Structure-Preserving Dynamics

arXiv:2508.11205v2 Announce Type: replace Abstract: Structure-preserving approaches to dynamics discovery have demonstrated great potential for modeling physical systems due to their use of strong ind

Meta says it will expand Instagram teen account safeguards to 27 EU countries, and plans to roll them out on Facebook in the US, ahead of the UK and EU in June (Foo Yun Chee/Reuters)

Foo Yun Chee / Reuters: Meta says it will expand Instagram teen account safeguards to 27 EU countries, and plans to roll them out on Facebook in the US, ahead of the UK and EU in June — Meta Platforms

safetytechmeme

Methods, Data, and Conceptual Change: Reflections from Two Quantitative Diachronic Case Studies

arXiv:2605.02052v1 Announce Type: new Abstract: This discussion paper reflects on how quantitative approaches to historical linguistics interact with dataset properties. Drawing on two worked examples

Local Ai

Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption

arXiv:2605.01137v1 Announce Type: new Abstract: Metric differential privacy (mDP) strengthens local differential privacy (LDP) by scaling noise to semantic distance, but many machine learning (ML) sys

local-aiarxiv-cs-lg

Metric Unreliability in Multimodal Machine Unlearning: A Systematic Analysis and Principled Unified Score

model-releasesarxiv-cs-cv

arXiv:2605.02206v1 Announce Type: new Abstract: Machine unlearning in Vision-Language Models (VLMs) is required for compliance with the General Data Protection Regulation (GDPR), yet current evaluatio

Mextsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation

model-releasesarxiv-cs-cv

arXiv:2605.02444v1 Announce Type: new Abstract: Encoder-decoder imbalance and the reliance on large input volumes make many 3D brain tumor segmentation models both compute-heavy and brittle. We presen

Micron closes up 11% after announcing its highest-capacity SSD has started to ship, lifting its market cap past $700B for the first time; Sandisk closes up 12% (Lola Murti/CNBC)

Lola Murti / CNBC: Micron closes up 11% after announcing its highest-capacity SSD has started to ship, lifting its market cap past 700B for the first time; Sandisk closes up 12% — Micron's historic ra

industrytechmeme

Microsoft at NSDI 2026: Advances in large-scale networked systems

researchmicrosoft-research

Microsoft researchers share advances in building and operating large-scale distributed systems, spanning datacenters, networking, and the growing intersection with AI during NSDI ’26. The post Microso

Microsoft gives up on Xbox Copilot AI

Xbox is 'winding down Copilot on mobile' and 'will stop development of Copilot on console,' new Xbox CEO Asha Sharma announced on Tuesday. The move follows Sharma's reorganization of the Xbox platform

industrythe-verge-ai

Microsoft's 2026 Work Trend Index: a survey of 20K AI users finds 65% fear falling behind, but only 13% report being rewarded for workplace AI experimentation (Todd Bishop/GeekWire)

Todd Bishop / GeekWire: Microsoft's 2026 Work Trend Index: a survey of 20K AI users finds 65% fear falling behind, but only 13% report being rewarded for workplace AI experimentation — [Editor's Note:

industrytechmeme

Middle-mile logistics through the lens of goal-conditioned reinforcement learning

arXiv:2605.02461v1 Announce Type: cross Abstract: Middle-mile logistics describes the problem of routing parcels through a network of hubs linked by trucks with finite capacity. We rephrase this as a

Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2605.00123v1 Announce Type: new Abstract: Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understa

Tutorials

MiniMax-M2.7 is now available across six inference providers on Artificial Analysis, with significant differentiation in speed and price @Sa…

tutorialsjeremy-howard--x

MiniMax-M2.7 is now available across six inference providers on Artificial Analysis, with significant differentiation in speed and price @SambaNovaAI leads on speed at 435 output tokens/s, >3x faster

Minimizing Collateral Damage in Activation Steering

arXiv:2605.01167v1 Announce Type: new Abstract: Activation steering is a method for controlling Large Language Model (LLM) behavior by intervening in its internal representations to increase the align

safetyarxiv-cs-lg

Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference

arXiv:2605.01579v1 Announce Type: cross Abstract: Empirical causal claims depend on many analyst decisions, from selecting covariates to choosing estimators. Existing robustness tools summarize how re

MIRA: A Score for Conditional Distribution Accuracy and Model Comparison

arXiv:2605.02014v1 Announce Type: cross Abstract: We introduce Mira, a sample-based score for assessing the accuracy of a candidate conditional distribution using only joint samples from the true data

safetyarxiv-cs-lg

MIRL: Mutual Information-Guided Reinforcement Learning for Vision-Language Models

arXiv:2605.01520v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) frequently suffer from visual perception errors and hallucinations that compromise answer accuracy in complex reasoning

Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability

arXiv:2605.01987v1 Announce Type: new Abstract: We study differential privacy (DP) in Graph Convolutional Networks (GCNs) through the framework of extit{subsampling stability}. We derive upper bounds

Missing from the “will AI replace doctors?” debate is that doctors (and lawyers and psychologists and bankers) all vote & form the donor bas…

applicationsethan-mollick--x

Missing from the “will AI replace doctors?” debate is that doctors (and lawyers and psychologists and bankers) all vote & form the donor base to political parties & have deep community ties. The gover

Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling

arXiv:2605.01676v1 Announce Type: cross Abstract: Missing data imputation remains a fundamental challenge in modern data science, especially when uncertainty quantification is essential. In this work,

Mitigating Misalignment Contagion by Steering with Implicit Traits

arXiv:2605.02751v1 Announce Type: cross Abstract: Language models (LMs) are increasingly used in high-stakes, multi-agent settings, where following instructions and maintaining value alignment are cri

safetyarxiv-cs-cl

Mitigating Multimodal LLMs Hallucinations via Relevance Propagation at Inference Time

arXiv:2605.01766v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have revolutionized the landscape of AI, demonstrating impressive capabilities in tackling complex vision and

Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection

arXiv:2605.02438v1 Announce Type: new Abstract: Open-set supervised anomaly detection (OSAD) aims to identify unseen anomalies using limited anomalous supervision. However, existing prototype-based me

MOC-3D: Manifold-Order Consistency for Text-to-3D Generation

arXiv:2605.01743v1 Announce Type: new Abstract: With the burgeoning development of fields such as the Metaverse, Virtual Reality (VR), and Digital Twins, text-to-3D generation has emerged as a researc

safetyarxiv-cs-cv

Model-Based Proactive Cost Generation for Learning Safe Policies Offline with Limited Violation Data

arXiv:2605.01356v1 Announce Type: new Abstract: Learning constraint-satisfying policies from offline data without risky online interaction is crucial for safety-critical decision making. Conventional

safetyarxiv-cs-lg

Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2602.04509v4 Announce Type: replace Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) on task-specific data is an effective way to improve performance on downstream applications. Ho

Model Merging: Foundations and Algorithms

arXiv:2605.01580v1 Announce Type: new Abstract: Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved

Model Organisms Are Leaky: Perplexity Differencing Often Reveals Finetuning Objectives

arXiv:2605.00994v1 Announce Type: new Abstract: Finetuning can significantly modify the behavior of large language models, including introducing harmful or unsafe behaviors. To study these risks, rese

MOGO: Residual Quantized Hierarchical Causal Transformer for High-Quality and Real-Time 3D Human Motion Generation

model-releasesarxiv-cs-cv

arXiv:2506.05952v4 Announce Type: replace Abstract: Recent advances in transformer-based text-to-motion generation have led to impressive progress in synthesizing high-quality human motion. Neverthele

Moira: Language-driven Hierarchical Reinforcement Learning for Pair Trading

arXiv:2605.01954v1 Announce Type: cross Abstract: Many sequential decision-making problems exhibit hierarchical structure, where high-level semantic choices constrain downstream actions and feedback i

applicationsarxiv-cs-cl

Molecular Representations for Large Language Models

arXiv:2605.01822v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being used to support scientific discovery. In chemistry, tasks such as reaction prediction and structure

MolmoAct2: Action Reasoning Models for Real-world Deployment

model-releasesarxiv-cs-ro

arXiv:2605.02881v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models aim to provide a single generalist controller for robots, but today's systems fall short on the criteria that matter

MolViBench: Evaluating LLMs on Molecular Vibe Coding

model-releasesarxiv-cs-cl

arXiv:2605.02351v1 Announce Type: new Abstract: Molecular Vibe Coding, a paradigm where chemists interact with LLMs to generate executable programs for molecular tasks, has emerged as a flexible alter

Momentum-Anchored Multi-Scale Fusion Model for Long-Tailed Chest X-Ray Classification

arXiv:2605.02292v1 Announce Type: new Abstract: Chest X-ray classification suffers from severe class imbalance where gradient updates bias toward majority classes, causing feature drift and poor perfo

safetyarxiv-cs-cv

MooD: An Efficient VA-Driven Affective Image Editing Framework via Fine-Grained Semantic Control

arXiv:2605.02521v1 Announce Type: new Abstract: Affective image editing (AIE) aims to edit visual content to evoke target emotions. However, existing methods often overlook inference efficiency and pr

More governments and public agencies should use HF and open-source AI in general. Let’s go sovereign AI!

More governments and public agencies should use HF and open-source AI in general. Let’s go sovereign AI! Cumhurbaşkanlığı İletişim Başkanlığımız, dünyanın en büyük yapay zekâ ve makine öğrenmesi toplu

industryclem-delangue--x

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation

model-releasesarxiv-cs-ro

arXiv:2507.14061v2 Announce Type: replace Abstract: What if a robot could rethink its own morphological representation to better meet the demands of diverse tasks? Most robotic systems today treat the

MOSAIC: Multi-agent Orchestration for Task-Intelligent Scientific Coding

model-releasesarxiv-cs-cl

arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding

Most AI tools are a black box. You put something in and have limited say over what happens in between. For production pipelines, that's a de…

Most AI tools are a black box. You put something in and have limited say over what happens in between. For production pipelines, that's a dealbreaker. Silverside, an AI innovation lab running full pro

applicationscomfyui--x

Motion-Aware Caching for Efficient Autoregressive Video Generation

arXiv:2605.01725v1 Announce Type: new Abstract: Autoregressive video generation paradigms offer theoretical promise for long video synthesis, yet their practical deployment is hindered by the computat

MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC

arXiv:2605.02509v1 Announce Type: new Abstract: Continual learning systems face a fundamental tension between plasticity -- acquiring new knowledge -- and stability -- retaining prior knowledge. We in

MSMixer: Learned Multi-Scale Temporal Mixing with Complementary Linear Shortcut for Long-Term Time Series Forecasting

arXiv:2605.02689v1 Announce Type: new Abstract: Long-term time series forecasting requires models that simultaneously capture rapid oscillations, medium-range periodicities, and slowly evolving macro-

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation

arXiv:2605.01374v1 Announce Type: new Abstract: Knowledge distillation is a key technique for compressing large language models (LLMs), but most existing methods align representations at fixed layers

safetyarxiv-cs-cl