All entries

MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents

model-releasesarxiv-cs-ai

arXiv:2509.06477v2 Announce Type: replace Abstract: Shortcuts such as APIs and deep-links have emerged as efficient complements to flexible GUI operations, fostering a promising hybrid paradigm for ML

Applications

Material-Agnostic Zero-Shot Thermal Inference for Metal Additive Manufacturing via a Parametric PINN Framework

DGX agent

arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio

applicationsarxiv-cs-lg

17 Apr 2026

Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips

arXiv:2502.07408v2 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) can be catastrophically disrupted by flipping only a handful of parameter bits. We introduce Deep Neural Lesion (D

Agents

MCPThreatHive: Automated Threat Intelligence for Model Context Protocol Ecosystems

arXiv:2604.13849v1 Announce Type: cross Abstract: The rapid proliferation of Model Context Protocol (MCP)-based agentic systems has introduced a new category of security threats that existing framewor

agentsarxiv-cs-ai

Mean Flow Policy Optimization

arXiv:2604.14698v1 Announce Type: new Abstract: Diffusion models have recently emerged as expressive policy representations for online reinforcement learning (RL). However, their iterative generative

Measuring multi-calibration

model-releasesarxiv-cs-lg

arXiv:2506.11251v2 Announce Type: replace-cross Abstract: A suitable scalar metric can help measure multi-calibration, defined as follows. When the expected values of observed responses are equal to c

MEBench: A Novel Benchmark for Understanding Mutual Exclusivity Bias in Vision-Language Models

arXiv:2505.20122v2 Announce Type: replace Abstract: This paper introduces MEBench, a novel benchmark for evaluating mutual exclusivity (ME) bias, a cognitive phenomenon observed in children during wor

Mechanistic Decoding of Cognitive Constructs in LLMs

arXiv:2604.14593v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate increasingly sophisticated affective capabilities, the internal mechanisms by which they process complex

MedVerse: Efficient and Reliable Medical Reasoning via DAG-Structured Parallel Execution

arXiv:2602.07529v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong performance and rapid progress in a wide range of medical reasoning tasks. However, their sequ

Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation

arXiv:2604.15190v1 Announce Type: cross Abstract: Simulating group-level user behavior enables scalable counterfactual evaluation of merchant strategies without costly online experiments. However, bui

MEME-Fusion@CHiPSAL 2026: Multimodal Ablation Study of Hate Detection and Sentiment Analysis on Nepali Memes

arXiv:2604.14218v1 Announce Type: new Abstract: Hate speech detection in Devanagari-scripted social media memes presents compounded challenges: multimodal content structure, script-specific linguistic

researcharxiv-cs-cl

MemGround: Long-Term Memory Evaluation Kit for Large Language Models in Gamified Scenarios

arXiv:2604.14158v1 Announce Type: new Abstract: Current evaluations of long-term memory in LLMs are fundamentally static. By fixating on simple retrieval and short-context inference, they neglect the

MetaDent: Labeling Clinical Images for Vision-Language Models in Dentistry

arXiv:2604.14866v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remains

Meta's AI spending spree is helping make its Quest headsets more expensive

Meta is raising the price of its entire Quest VR headset lineup due to an AI-driven squeeze on components required to make the headsets. Memory chips are in high demand from AI infrastructure expansio

industryars-technica

Applications

Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation

arXiv:2604.15101v1 Announce Type: cross Abstract: Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents bas

applicationsarxiv-cs-lg

Metric-Aware Principal Component Analysis (MAPCA):A Unified Framework for Scale-Invariant Representation Learning

arXiv:2604.14249v1 Announce Type: new Abstract: We introduce Metric-Aware Principal Component Analysis (MAPCA), a unified framework for scale-invariant representation learning based on the generalised

Applications

Million of recipes. Fuzzy ingredient data. One afternoon to solve it. 🍳⚡ Will Templeton, CTO and co-founder at Allspice, explains why Pinec…

Million of recipes. Fuzzy ingredient data. One afternoon to solve it. 🍳⚡ Will Templeton, CTO and co-founder at Allspice, explains why Pinecone is their fundamental building block: ❌ No weeks of cluste

applicationspinecone--x

Agents

MIND: AI Co-Scientist for Material Research

arXiv:2604.13699v1 Announce Type: cross Abstract: Large language models (LLMs) have enabled agentic AI systems for scientific discovery, but most approaches remain limited to textbased reasoning witho

agentsarxiv-cs-ai

MinShap: A Modified Shapley Value Approach for Feature Selection

arXiv:2604.15107v1 Announce Type: cross Abstract: Feature selection is a classical problem in statistics and machine learning, and it continues to remain an extremely challenging problem especially in

MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data

arXiv:2603.22564v2 Announce Type: replace Abstract: Understanding cellular trajectories via time-resolved single-cell transcriptomics is vital for studying development, regeneration, and disease. A ke

MIT engineers built an AI wristband that controls robots by reading your hand muscles. It works by using an ultrasound to capture images of …

MIT engineers built an AI wristband that controls robots by reading your hand muscles. It works by using an ultrasound to capture images of the muscles and tendons in your wrist. An AI algorithm then

industryrowan-cheung--x

Mitigating LLM biases toward spurious social contexts using direct preference optimization

arXiv:2604.02585v2 Announce Type: replace-cross Abstract: LLMs are increasingly used for high-stakes decision-making, yet their sensitivity to spurious contextual information can introduce harmful bia

MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining

arXiv:2604.14198v1 Announce Type: cross Abstract: Domain reweighting can improve sample efficiency and downstream generalization, but data-mixture optimization for multimodal midtraining remains large

ML-based approach to classification and generation of structured light propagation in turbulent media

arXiv:2604.14208v1 Announce Type: cross Abstract: This work develops machine learning approaches to classify structured light wave beams developing random speckle disturbances as they propagate throug

MLDAS: Machine Learning Dynamic Algorithm Selection for Software-Defined Networking Security

arXiv:2604.14957v1 Announce Type: cross Abstract: Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their per

MM-WebAgent: A Hierarchical Multimodal Web Agent for Webpage Generation

arXiv:2604.15309v1 Announce Type: cross Abstract: The rapid progress of Artificial Intelligence Generated Content (AIGC) tools enables images, videos, and visualizations to be created on demand for we

Model-Based Reinforcement Learning Exploits Passive Body Dynamics for High-Performance Biped Robot Locomotion

arXiv:2604.14565v1 Announce Type: new Abstract: Embodiment is a significant keyword in recent machine learning fields. This study focused on the passive nature of the body of a biped robot to generate

researcharxiv-cs-ro

Applications

Model-Based Reinforcement Learning under Random Observation Delays

arXiv:2509.20869v2 Announce Type: replace Abstract: Delays frequently occur in real-world environments, yet standard reinforcement learning (RL) algorithms often assume instantaneous perception of the

applicationsarxiv-cs-lg

Hardware

Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3

arXiv:2603.27844v2 Announce Type: replace Abstract: Majority voting over multiple LLM attempts improves mathematical reasoning, but correlated errors limit the effective sample size. A natural fix is

hardwarearxiv-cs-cl

Model-Free Assessment of Simulator Fidelity via Quantile Curves

arXiv:2512.05024v3 Announce Type: replace-cross Abstract: As generative AI models are increasingly used to simulate real-world systems, quantifying the ``sim-to-real'' gap is critical. For each input

Modeling LLM Unlearning as an Asymmetric Two-Task Learning Problem

arXiv:2604.14808v1 Announce Type: new Abstract: Machine unlearning for large language models (LLMs) aims to remove targeted knowledge while preserving general capability. In this paper, we recast LLM

Modular Continual Learning via Zero-Leakage Reconstruction Routing and Autonomous Task Discovery

model-releasesarxiv-cs-lg

arXiv:2604.14375v1 Announce Type: new Abstract: Catastrophic forgetting remains a primary hurdle in sequential task learning for artificial neural networks. We propose a silicon-native modular archite

ModuSeg: Decoupling Object Discovery and Semantic Retrieval for Training-Free Weakly Supervised Segmentation

arXiv:2604.07021v2 Announce Type: replace Abstract: Weakly supervised semantic segmentation aims to achieve pixel-level predictions using image-level labels. Existing methods typically entangle semant

Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios

arXiv:2604.14986v1 Announce Type: new Abstract: Safe and efficient assistive planning for visually impaired scenarios remains challenging, since existing methods struggle with multi-objective optimiza

safetyarxiv-cs-ro

Local Ai

MS-SSE-Net: A Multi-Scale Spatial Squeeze-and-Excitation Network for Structural Damage Detection in Civil and Geotechnical Engineering

arXiv:2604.14711v1 Announce Type: new Abstract: Structural damage detection is essential for maintaining the safety and reliability of civil infrastructure. However, accurately identifying different t

local-aiarxiv-cs-cv

Multi-Modal Manipulation via Multi-Modal Policy Consensus

arXiv:2509.23468v3 Announce Type: replace-cross Abstract: Effectively integrating diverse sensory modalities is crucial for robotic manipulation. However, the typical approach of feature concatenation

Multi-Persona Thinking for Bias Mitigation in Large Language Models

arXiv:2601.15488v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit social biases, which can lead to harmful stereotypes and unfair outcomes. We propose extbf{Multi-Persona Thinki

Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits

arXiv:2604.14908v1 Announce Type: new Abstract: We study downlink beam and rate adaptation in a multi-user mmWave MISO system where multiple base stations (BSs), each using analog beamforming from fin

Multigrain-aware Semantic Prototype Scanning and Tri-Token Prompt Learning Embraced High-Order RWKV for Pan-Sharpening

arXiv:2604.14622v1 Announce Type: new Abstract: In this work, we propose a Multigrain-aware Semantic Prototype Scanning paradigm for pan-sharpening, built upon a high-order RWKV architecture and a tri

NanoClaw partners with Vercel to deliver one-click approvals for AI agents working on sensitive tasks

NanoCo, the startup behind NanoClaw, a fast-growing alternative to OpenAI Group PBC’s OpenClaw project, said today it’s teaming up with Vercel Inc. and OneCLI to try to fix the “trust problem” holding

industrysiliconangle

Hardware

Nautilus: An Auto-Scheduling Tensor Compiler for Efficient Tiled GPU Kernels

arXiv:2604.14825v1 Announce Type: cross Abstract: We present Nautilus, a novel tensor compiler that moves toward fully automated math-to-kernel optimization. Nautilus compiles a high-level algebraic s

hardwarearxiv-cs-lg

NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning

arXiv:2604.15076v1 Announce Type: new Abstract: To navigate a space, the brain makes an internal representation of the environment using different cells such as place cells, grid cells, head direction

researcharxiv-cs-ro

Netflix plans to launch a vertical video feed, to help with content discovery, this month, and plans to use AI for content creation and recommendations (Ivan Mehta/TechCrunch)

Ivan Mehta / TechCrunch: Netflix plans to launch a vertical video feed, to help with content discovery, this month, and plans to use AI for content creation and recommendations — Netflix is going to l

industrytechmeme

Neuro-Oracle: A Trajectory-Aware Agentic RAG Framework for Interpretable Epilepsy Surgical Prognosis

arXiv:2604.14216v1 Announce Type: cross Abstract: Predicting post-surgical seizure outcomes in pharmacoresistant epilepsy is a clinical challenge. Conventional deep-learning approaches operate on stat

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities

arXiv:2509.06921v2 Announce Type: replace-cross Abstract: Cybersecurity demands both rapid pattern recognition and deliberative reasoning, yet purely neural or purely symbolic approaches each address

safetyarxiv-cs-ai

NG-GS: NeRF-Guided 3D Gaussian Splatting Segmentation

arXiv:2604.14706v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accur

safetyarxiv-cs-cv

NLP needs Diversity outside of 'Diversity'

arXiv:2604.14595v1 Announce Type: new Abstract: This position paper argues that recent progress with diversity in NLP is disproportionately concentrated on a small number of areas surrounding fairness

No More Guessing: a Verifiable Gradient Inversion Attack in Federated Learning

arXiv:2604.15063v1 Announce Type: new Abstract: Gradient inversion attacks threaten client privacy in federated learning by reconstructing training samples from clients' shared gradients. Gradients ag