Search: “models”

arXiv:2606.22002v1 Announce Type: new Abstract: Training medical image classifiers on entire datasets is wasteful when annotation budgets are limited: not all samples contribute equally, yet acquiring

arXiv:2606.21669v1 Announce Type: new Abstract: Robust locomotion and navigation for legged robots relies heavily on dependable odometry. Traditional multi-sensor fusion for such state estimation requ

arXiv:2606.22174v1 Announce Type: new Abstract: Whole-body humanoid loco-manipulation requires coordinating the robot's entire kinematic chain. However, most existing systems typically decouple the up

arXiv:2606.21381v1 Announce Type: new Abstract: Deep learning in computational microscopy is severely constrained by the scarcity of densely annotated datasets. While synthetic data generation has bri

arXiv:2606.20621v1 Announce Type: cross Abstract: Multi-agent debate improves the reliability of large language models (LLMs) through iterative peer critiques. However, fixed topologies often introduc

arXiv:2606.21596v1 Announce Type: new Abstract: Reconstructing compositional 3D scenes from a single image is a fundamental challenge in 3D world modeling. Recent methods can recover high-fidelity, co

arXiv:2606.21162v1 Announce Type: cross Abstract: 3D human avatars have shown impressive visual fidelity driven by pose-conditioned models, yet they still lack the physical ability required for intera

arXiv:2606.23175v1 Announce Type: new Abstract: AI scientist systems are described as tools, coauthors, or founders, but we evaluate them as if only the final answer matters. This position paper argue

arXiv:2606.21896v1 Announce Type: cross Abstract: Solar flares, particularly those of the M- and X-class, have a significant impact on human life because of their potential to disrupt critical infrast

arXiv:2606.21994v1 Announce Type: new Abstract: On-policy distillation (OPD) improves reasoning models by applying dense teacher supervision on student-sampled trajectories. However, scaling OPD to lo

arXiv:2606.23673v1 Announce Type: cross Abstract: Mental health assessment commonly relies on isolated screening instruments or data-driven models that often lack interpretability and multi-dimensiona

The Drivetrain Approach is a framework for building effective data products, developed by Jeremy Howard and published by O'Reilly Media, that focuses on defining business objectives, identifying lever

arXiv:2606.22749v1 Announce Type: new Abstract: Pre-trained Vision Foundation Models (VFMs) have become central to modern computer vision due to their powerful semantic representations and strong gene

arXiv:2606.20712v1 Announce Type: new Abstract: Sampling-based Model Predictive Control (SMPC) is a promising strategy for contact-rich robotic manipulation, combining gradient-free optimization with

arXiv:2603.19925v2 Announce Type: replace-cross Abstract: Whole slide image (WSI) analysis heavily relies on multiple instance learning (MIL). While recent methods benefit from large-scale foundation

arXiv:2606.21179v1 Announce Type: new Abstract: Soil properties relevant to agricultural and environmental applications are conventionally measured using elaborate laboratory methods involving physica

arXiv:2606.20980v1 Announce Type: new Abstract: As Self-Driving Cars continue to expand internationally and use multi-modal systems such as VLMs as a cognitive backbone for their Action models; how we

arXiv:2606.21786v1 Announce Type: new Abstract: We introduce RocketPFN, a training-free pipeline for time series classification that combines random convolutional feature extraction (Rocket) with in-c

arXiv:2606.23267v1 Announce Type: new Abstract: Flow matching has recently emerged as a strong paradigm for state-of-the-art text-to-image (T2I) generation, enabling high-quality generation with a sma

Sakana AI's Fugu is a technical report describing an AI model or system, likely focusing on neural architecture design or evolutionary computation methods given Sakana AI's research focus. The report

arXiv:2606.22984v1 Announce Type: cross Abstract: Efficient sampling of the Boltzmann distribution in frustrated spin glasses is central to statistical mechanics and combinatorial optimization. Despit

arXiv:2601.20209v2 Announce Type: replace Abstract: Reinforcement learning has empowered large language models to act as intelligent agents, yet training them for long-horizon tasks remains challengin

arXiv:2606.22639v1 Announce Type: cross Abstract: Contextual bandit algorithms have transformed modern experimentation by enabling real-time adaptation for personalized treatment. Yet these advantages

arXiv:2511.14445v2 Announce Type: replace-cross Abstract: We present Tell Me, a mental well-being system that leverages advances in large language models to provide accessible, context-aware support f

arXiv:2606.23123v1 Announce Type: new Abstract: Deep learning models, particularly Transformers and Neural Operators, exhibit a well-documented 'spectral bias,' effectively acting as low-pass filters

This post likely argues that modern AI systems are shifting focus from modeling human cognition and reasoning to instead learning from and operating within the complexities of the real world and physi

arXiv:2606.22959v1 Announce Type: cross Abstract: Latent diffusion approaches to sign language production (SLP) rely on an initial stage that learns an encoding of sign pose sequences, enabling genera

arXiv:2606.21514v1 Announce Type: new Abstract: Recently, Muon has gained substantial attention as an appealing alternative to Adam-like optimizers, with many works highlighting its advantages through

arXiv:2606.23286v1 Announce Type: new Abstract: Sorting a huge stream of waste accurately within a short period can be done with the support of digitalization, particularly Artificial Intelligence, in

arXiv:2508.05762v3 Announce Type: replace-cross Abstract: Universal machine learning force fields (UMLFFs) promise to revolutionize materials science by enabling rapid atomistic simulations across the

arXiv:2606.23204v1 Announce Type: new Abstract: Large-scale image-text datasets, such as LAION-5B, are foundational to modern AI systems, yet their vast scale and uncurated nature raise significant co

arXiv:2606.20711v1 Announce Type: new Abstract: UI videos provide a natural input for generating interactive webpages, as they capture both webpage appearance and action-triggered state transitions. H

arXiv:2606.22870v1 Announce Type: new Abstract: Recent advancements in chain-of-thought (CoT) reasoning have shown promise in enhancing video understanding and reasoning capabilities of multimodal lar

arXiv:2606.20728v1 Announce Type: new Abstract: Vision foundation tools such as open-vocabulary detectors, segmentation models, and post-processing operators are powerful building blocks for computer

arXiv:2606.16196v2 Announce Type: replace-cross Abstract: Deep neural networks have achieved remarkable performance across medical imaging tasks, yet their tendency to overgeneralize under distributio

you need docs built for agents Docs are the eyes and ears of Agents. But we're moving so fast that they are always outdated. So hence an outdated doc also confuses the models. But it's also hard keep

In this post, you will learn how Ampersend built a pay-per-intelligence routing layer on top of Amazon Bedrock AgentCore Payments. AI agents autonomously route tasks to the most effective model, pay p

This guide from OpenAI covers techniques for optimizing the use of Codex (their code generation model) for extended programming tasks and projects that require sustained AI assistance. It likely discu

Deep Agents v0.6 feature spotlight: a code interpreter. Agents can now call tools from inside a runtime, keep intermediate results out of model context, and only pass the relevant output back. Fewer r

The US government ordered Anthropic to cut off foreign access to its Mythos 5 and Claude Fable 5 AI models in June 2026, citing national security concerns related to jailbreak vulnerabilities that cou

This post appears to announce or celebrate the discovery or successful implementation of Ollama, a tool for running large language models locally. Based on the enthusiastic tone and source, it likely

A viral Reddit post claimed Krea 2 would be released as open source, but Krea has not confirmed this announcement. Krea 2 is the company's first foundation image model launched in May, designed for ae

Automated lint: 48 errors, 13 warnings, 3 info

LLMs can’t be trusted to follow rules. Which means they can’t be trusted, period. If we are going to solve alignment we must move on. Large language models can be persuaded to break their own rules. N

New piece in @TheAtlantic! We always hear that AI will cure cancer, and I would immediately benefit if it did. But I argue that racing ahead on generalist AI models creates unclear benefits for cancer

Satya Nadella says the public wouldn't tolerate a few AI labs 'doing all of the learning for the world', as Microsoft moves to provide low-cost models and tools (Wall Street Journal) (Visit Techmeme d