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Making ChatGPT better for clinicians

OpenAI describes improvements and adaptations made to ChatGPT to better serve clinical and healthcare professionals. The work likely addresses how the model can be made more reliable, accurate, and us

model-releasesopenai

Mango: Multi-Agent Web Navigation via Global-View Optimization

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arXiv:2604.18779v1 Announce Type: new Abstract: Existing web agents typically initiate exploration from the root URL, which is inefficient for complex websites with deep hierarchical structures. Witho

model-releasesarxiv-cs-cl

22 Apr 2026

Tutorials

MapPFN: Learning Causal Perturbation Maps in Context

arXiv:2601.21092v2 Announce Type: replace Abstract: Planning effective interventions in biological systems requires treatment-effect models that adapt to unseen biological contexts by identifying thei

tutorialsarxiv-cs-lg

Mask World Model: Predicting What Matters for Robust Robot Policy Learning

arXiv:2604.19683v1 Announce Type: new Abstract: World models derived from large-scale video generative pre-training have emerged as a promising paradigm for generalist robot policy learning. However,

safetyarxiv-cs-ro

MATA: Multi-Agent Framework for Reliable and Flexible Table Question Answering

arXiv:2602.09642v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have significantly improved table understanding tasks such as Table Question Answering (TableQ

agentsarxiv-cs-ai

Match-Any-Events: Zero-Shot Motion-Robust Feature Matching Across Wide Baselines for Event Cameras

arXiv:2604.18744v1 Announce Type: new Abstract: Event cameras have recently shown promising capabilities in instantaneous motion estimation due to their robustness to low light and fast motions. Howev

Maximizing Gemini: Google Cloud makes its bid to build the operating system for enterprise AI

model-releasessiliconangle

Google LLC has emerged as the only cloud “hyperscaler” with a leading frontier artificial intelligence large language model – Gemini – and today it issued a raft of announcements designed to capitaliz

Mechanistic Anomaly Detection via Functional Attribution

model-releasesarxiv-cs-lg

arXiv:2604.18970v1 Announce Type: new Abstract: We can often verify the correctness of neural network outputs using ground truth labels, but we cannot reliably determine whether the output was produce

MedFlowSeg: Flow Matching for Medical Image Segmentation with Frequency-Aware Attention

arXiv:2604.19675v1 Announce Type: new Abstract: Flow matching has recently emerged as a principled framework for learning continuous-time transport maps, enabling efficient deterministic generation wi

🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power! Yes, 27B, and Qwen3.6-27B punches way above i…

model-releasesjeremy-howard--x

🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power! Yes, 27B, and Qwen3.6-27B punches way above its weight. 👇 What's new: 🧠 Outstanding agentic coding — surpa

Memory Assignment for Finite-Memory Strategies in Adversarial Patrolling Games

arXiv:2505.14137v2 Announce Type: replace Abstract: Adversarial Patrolling games form a subclass of Security games where a Defender moves between locations, guarding vulnerable targets. The main algor

researcharxiv-cs-ai

Local Ai

Memory Over Maps: 3D Object Localization Without Reconstruction

arXiv:2603.20530v2 Announce Type: replace-cross Abstract: Target localization is a prerequisite for embodied tasks such as navigation and manipulation. Conventional approaches rely on constructing exp

local-aiarxiv-cs-cv

Tools

Mention @Cursor to kick off tasks in Slack and see updates of its work streaming in real time. Cursor uses context in the thread and broade…

Cursor can be mentioned in Slack threads to initiate automated tasks, with real-time streaming updates of task progress visible within the conversation. The integration leverages thread context and br

toolscursor--x

Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems

arXiv:2604.19540v1 Announce Type: cross Abstract: Teams of LLM agents increasingly collaborate on tasks spanning days or weeks: multi-day data-generation sprints where generator, reviewer, and auditor

agentsarxiv-cs-ai

Meta unveils Live Chats on Threads for real-time conversations during cultural events, launching first within the NBA Threads community during the playoffs (Aisha Malik/TechCrunch)

Aisha Malik / TechCrunch: Meta unveils Live Chats on Threads for real-time conversations during cultural events, launching first within the NBA Threads community during the playoffs — Threads is launc

industrytechmeme

Michele Catasta (@pirroh) at Google Cloud Next talking about what's new with Gemini, agentic applications, and what's next for builders. Fre…

Michele Catasta (@pirroh) at Google Cloud Next talking about what's new with Gemini, agentic applications, and what's next for builders. Fresh off Replit being named Google Cloud Partner of the Year.

model-releasesreplit--x

Micro Language Models Enable Instant Responses

model-releasesarxiv-cs-cl

arXiv:2604.19642v1 Announce Type: new Abstract: Edge devices such as smartwatches and smart glasses cannot continuously run even the smallest 100M-1B parameter language models due to power and compute

Microsoft issues emergency update for macOS and Linux ASP.NET threat

Microsoft issued an emergency update for ASP.NET Core

industryars-technica

Microsoft plans to invest AU$25B by 2029 to expand Azure AI supercomputing and cloud infrastructure in Australia, its largest commitment to the country (Ainslie Chandler/Bloomberg)

Ainslie Chandler / Bloomberg: Microsoft plans to invest AU25B by 2029 to expand Azure AI supercomputing and cloud infrastructure in Australia, its largest commitment to the country — Microsoft Corp. a

industrytechmeme

Mind the (DH) Gap! A Contrast in Risky Choices Between Reasoning and Conversational LLMs

arXiv:2602.15173v2 Announce Type: replace Abstract: The use of large language models either as decision support systems, or in agentic workflows, is rapidly transforming the digital ecosystem. However

agentsarxiv-cs-ai

Mind the Unseen Mass: Unmasking LLM Hallucinations via Soft-Hybrid Alphabet Estimation

arXiv:2604.19162v1 Announce Type: new Abstract: This paper studies uncertainty quantification for large language models (LLMs) under black-box access, where only a small number of responses can be sam

researcharxiv-cs-cl

Mind2Drive: Predicting Driver Intentions from EEG in Real-world On-Road Driving

arXiv:2604.19368v1 Announce Type: new Abstract: Predicting driver intention from neurophysiological signals offers a promising pathway for enhancing proactive safety in advanced driver assistance syst

MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling

model-releasesarxiv-cs-cl

arXiv:2511.11793v3 Announce Type: replace Abstract: We present MiroThinker v1.0, an open-source research agent designed to advance tool-augmented reasoning and information-seeking capabilities. Unlike

MIT researchers just replicated human muscles with AI-controlled fibers. Inside each fiber is a sealed tube of electrically charged liquid a…

MIT researchers just replicated human muscles with AI-controlled fibers. Inside each fiber is a sealed tube of electrically charged liquid and a tiny electric pump. When the pump activates, one side c

industryrowan-cheung--x

MiTA Attention: Efficient Fast-Weight Scaling via a Mixture of Top-k Activations

arXiv:2602.01219v4 Announce Type: replace-cross Abstract: The attention operator in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically instantiated from input tok

Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling

arXiv:2510.08145v2 Announce Type: replace Abstract: Large Language Models (LLMs) as automatic evaluators, commonly referred to as LLM-as-a-Judge, have also attracted growing attention. This approach p

safetyarxiv-cs-cl

Mitigating Long-Tail Bias via Prompt-Controlled Diffusion Augmentation

arXiv:2602.04749v2 Announce Type: replace Abstract: Long-tailed class imbalance remains a fundamental obstacle in semantic segmentation of high-resolution remote-sensing imagery, where dominant classe

Mixture of Predefined Experts: Maximizing Data Usage on Vertical Federated Learning

arXiv:2602.12708v2 Announce Type: replace Abstract: Vertical Federated Learning (VFL) has emerged as a critical paradigm for collaborative model training in privacy-sensitive domains such as finance a

safetyarxiv-cs-lg

ml-intern by @huggingface is wild 🔥 You drop a high-level prompt (“build the best scientific reasoning model” or “crush healthcare benchmar…

model-releasesclem-delangue--x

ml-intern by @huggingface is wild 🔥 You drop a high-level prompt (“build the best scientific reasoning model” or “crush healthcare benchmarks”) and this open-source agent does the entire post-training

MMControl: Unified Multi-Modal Control for Joint Audio-Video Generation

arXiv:2604.19679v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) have enabled high-quality joint audio-video generation, producing videos with synchronized audio within

Model-Agnostic Meta Learning for Class Imbalance Adaptation

arXiv:2604.18759v1 Announce Type: new Abstract: Class imbalance is a widespread challenge in NLP tasks, significantly hindering robust performance across diverse domains and applications. We introduce

researcharxiv-cs-cl

Tutorials

Modelling and Analysing Behaviours and Emotions via Complex User Interactions

arXiv:1902.07683v1 Announce Type: cross Abstract: Over the past 15 years, the volume, richness and quality of data collected from the combined social networking platforms has increased beyond all expe

tutorialsarxiv-cs-ai

Monk, which automates accounts receivable workflows, raised a 25M Series A co-led by Footwork and Acrew Capital, bringing its total funding to 29M (Ryan Lawler/Axios)

Ryan Lawler / Axios: Monk, which automates accounts receivable workflows, raised a 25M Series A co-led by Footwork and Acrew Capital, bringing its total funding to 29M — Monk, which automates accounts

industrytechmeme

MoonSeg3R: Monocular Online Zero-Shot Segment Anything in 3D with Reconstructive Foundation Priors

arXiv:2512.15577v2 Announce Type: replace Abstract: In this paper, we focus on online zero-shot monocular 3D instance segmentation, a novel practical setting where existing approaches fail to perform

MORPHOGEN: A Multilingual Benchmark for Evaluating Gender-Aware Morphological Generation

model-releasesarxiv-cs-ai

arXiv:2604.18914v1 Announce Type: cross Abstract: While multilingual large language models (LLMs) perform well on high-level tasks like translation and question answering, their ability to handle gram

MOSA: Motion-Guided Semantic Alignment for Dynamic Scene Graph Generation

arXiv:2604.19631v1 Announce Type: new Abstract: Dynamic Scene Graph Generation (DSGG) aims to structurally model objects and their dynamic interactions in video sequences for high-level semantic under

MRS: Multi-Resolution Skills for HRL Agents

arXiv:2505.21410v2 Announce Type: replace Abstract: Hierarchical reinforcement learning (HRL) decomposes the policy into a manager and a worker, enabling long-horizon planning but introducing a perfor

MSDS: Deep Structural Similarity with Multiscale Representation

model-releasesarxiv-cs-cv

arXiv:2604.19159v1 Announce Type: new Abstract: Deep-feature-based perceptual similarity models have demonstrated strong alignment with human visual perception in Image Quality Assessment (IQA). Howev

Tutorials

Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming

arXiv:2604.19670v1 Announce Type: cross Abstract: Effective human-robot teaming is crucial for the practical deployment of robots in human workspaces. However, optimizing joint human-robot plans remai

tutorialsarxiv-cs-ai

Multi-Domain Learning with Global Expert Mapping

model-releasesarxiv-cs-cv

arXiv:2604.18842v1 Announce Type: new Abstract: Human perception generalizes well across different domains, but most vision models struggle beyond their training data. This gap motivates multi-dataset

Multi-Gait Learning for Humanoid Robots Using Reinforcement Learning with Selective Adversarial Motion Prior

arXiv:2604.19102v1 Announce Type: cross Abstract: Learning diverse locomotion skills for humanoid robots in a unified reinforcement learning framework remains challenging due to the conflicting requir

Local Ai

Multi-Level Temporal Graph Networks with Local-Global Fusion for Industrial Fault Diagnosis

arXiv:2604.18765v1 Announce Type: cross Abstract: Fault detection and diagnosis are critical for the optimal and safe operation of industrial processes. The correlations among sensors often display no

local-aiarxiv-cs-ai

Multi-modal Reasoning with LLMs for Visual Semantic Arithmetic

arXiv:2604.19567v1 Announce Type: new Abstract: Reinforcement learning (RL) as post-training is crucial for enhancing the reasoning ability of large language models (LLMs) in coding and math. However,

Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration

model-releasesarxiv-cs-ai

arXiv:2604.19093v1 Announce Type: cross Abstract: Multi-modal test-time adaptation (TTA) enhances the resilience of benchmark multi-modal models against distribution shifts by leveraging the unlabeled

Multi-Step Gaussian Process Propagation for Adaptive Path Planning

arXiv:2604.19148v1 Announce Type: new Abstract: Efficient and robust path planning hinges on combining all accessible information sources. In particular, the task of path planning for robotic environm

agentsarxiv-cs-ro

Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge

arXiv:2603.11665v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have been widely adopted as MLLM-as-a-Judges due to their strong alignment with human judgment across vario

safetyarxiv-cs-cl

Applications

Multi-view Crowd Tracking Transformer with View-Ground Interactions Under Large Real-World Scenes

arXiv:2604.19318v1 Announce Type: new Abstract: Multi-view crowd tracking estimates each person's tracking trajectories on the ground of the scene. Recent research works mainly rely on CNNs-based mult

applicationsarxiv-cs-cv

Multiclass Local Calibration with the Jensen-Shannon Distance

arXiv:2510.26566v2 Announce Type: replace-cross Abstract: Developing trustworthy Machine Learning (ML) models requires their predicted probabilities to be well-calibrated, meaning they should reflect