Search: “applications”

Ternary Decision Trees with Locally-Adaptive Uncertainty Zones

arXiv:2605.22740v1 Announce Type: new Abstract: Decision trees partition the feature space using hard binary thresholds, assigning identical confidence to instances far from a decision boundary and to

23 May 2026

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DGX agent

arXiv:2603.04525v2 Announce Type: replace-cross Abstract: Modern approaches for learning from non-Markovian time series, such as recurrent neural networks, neural controlled differential equations or

model-releasesarxiv-cs-lg

23 May 2026

AgroTools: A Benchmark for Tool-Augmented Multimodal Agents in Agriculture

model-releasesarxiv-cs-cv

arXiv:2605.22366v1 Announce Type: new Abstract: Agricultural decision-making increasingly requires multimodal systems that can transform visual observations into reliable, executable actions. However,

AgroVG: A Large-Scale Multi-Source Benchmark for Agricultural Visual Grounding

model-releasesarxiv-cs-cv

arXiv:2605.22034v1 Announce Type: new Abstract: Visual grounding, the task of localizing objects described by natural-language expressions, is a foundational capability for agricultural AI systems, en

Tools

[AINews] New AI Infra unicorns: Exa, Modal, TurboPuffer

This article discusses three AI infrastructure startups—Exa, Modal, and TurboPuffer—that have recently achieved unicorn status (valued at $1 billion or more). The piece likely covers their funding rou

toolslatent-space

Industry

Blockchain.com files confidentially for US IPO amid growing crypto listings

United Kingdom-based Blockchain.com Group Holdings Inc., a cryptocurrency exchange and wallet service, announced Thursday that it has filed confidentially for an initial public offering in the United

industrysiliconangle

Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection

arXiv:2605.22605v1 Announce Type: cross Abstract: Object detection from Unmanned Aerial Vehicles (UAVs) is challenged by severe ego-motion, camera jitter, and large scale variations. While modern dete

Diffusion-guided Generalizable Enhancer for Urban Scene Reconstruction

arXiv:2605.22420v1 Announce Type: new Abstract: Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural re

agentsarxiv-cs-cv

Enabling Regulatory Multi-Agent Collaboration: Architecture, Challenges, and Solutions

arXiv:2509.09215v2 Announce Type: replace Abstract: Large language models (LLMs)-empowered autonomous agents are transforming both digital and physical environments by enabling adaptive, multi-agent c

agentsarxiv-cs-ai

Enhancing Multimodal Large Language Models for Safety-Critical Driving Video Analysis

arXiv:2605.22185v1 Announce Type: new Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding. However, thei

safetyarxiv-cs-cv

Evaluating Clinical Competencies of Large Language Models with a General Practice Benchmark

arXiv:2503.17599v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated considerable potential in general practice. However, existing benchmarks and evaluation frameworks pr

Harder to Defend: Towards Chinese Toxicity Attacks via Implicit Enhancement and Obfuscation Rewriting

arXiv:2605.22258v1 Announce Type: new Abstract: Large language models (LLMs) require robust toxicity evaluation beyond explicit wording. This setting remains underexplored in Chinese, where toxicity m

Tutorials

Harvard University just voted to limit the number of A grades given in undergraduate classes to about 20% of the class. I’m not in favor of …

Harvard University just voted to limit the number of A grades given in undergraduate classes to about 20% of the class. I’m not in favor of this. It deeply runs counter to how I believe education shou

tutorialsandrew-ng--x

Heartbeat-Bound Hierarchical Credentials: Cryptographic Revocation for AI Agent Swarms

arXiv:2605.20704v1 Announce Type: cross Abstract: Autonomous AI agents that spawn sub-agent swarms create a safety gap: existing credential revocation mechanisms, OAuth~2.0 introspection, OCSP, and W3

local-aiarxiv-cs-ai

img2vid: ComfyUI doesn't find the spatial upscaler

local-air-stablediffusion

This Reddit post discusses a common ComfyUI issue where users cannot locate spatial upscaler models for img2vid workflows. The problem typically stems from placing spatial upscaler models in the wrong

Label tree semantic losses for rich multi-class medical image segmentation

arXiv:2507.15777v3 Announce Type: replace Abstract: Rich and accurate medical image segmentation is poised to underpin the next generation of AI-defined clinical practice by delineating critical anato

Open-World Evaluations for Measuring Frontier AI Capabilities

model-releasesarxiv-cs-ai

arXiv:2605.20520v1 Announce Type: new Abstract: Benchmark-based evaluation remains important for tracking frontier AI progress. But it can both overstate and understate deployed capability because it

Polite on the Surface, Wrong in Practice: A Curated Dataset for Fixing Honorific Failures in Multilingual Bangla Generation

arXiv:2605.22487v1 Announce Type: new Abstract: Recent advances in Multilingual Large Language Models (MLLMs) have significantly enhanced cross-lingual conversational capabilities, yet modeling cultur

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks

arXiv:2605.22351v1 Announce Type: new Abstract: Low-bit quantization is widely used to compress super-resolution (SR) models and reduce storage and computation costs for deployment on resource-limited

safetyarxiv-cs-cv

RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization

arXiv:2509.23582v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) have recently emerged as a powerful backbone for image generation, demonstrating superior scalability and performance

SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning

arXiv:2506.14648v2 Announce Type: replace Abstract: Preference-based Reinforcement Learning (PbRL) methods provide a solution to avoid reward engineering by learning reward models based on human prefe

safetyarxiv-cs-ro

SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm

arXiv:2602.08064v2 Announce Type: replace-cross Abstract: The long-standing tension between Pre- and Post-Norm remains an open problem in Transformer architecture, reflecting a fundamental trade-off b

Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning

arXiv:2605.22748v1 Announce Type: new Abstract: Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, dynamic real-world spaces. This f

safetyarxiv-cs-ro

VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals

arXiv:2605.20742v1 Announce Type: new Abstract: With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly

local-aiarxiv-cs-ai

We are making our discount permanent! 🎉 Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀

model-releasesjeremy-howard--x

DeepSeek has announced a permanent discount for its DeepSeek-V4-Pro model, encouraging developers to build and innovate with the platform. The announcement was made via social media and emphasizes the

Industry

what problem do you most hope AI will solve in the future? maybe we can help!

Sam Altman posed a question to the public asking what problem they most hope AI will solve in the future, with an implied offer that OpenAI might be able to help address it. The post invites community

industrysam-altman--x

A 10,000-Year Global Stochastic Tropical Cyclone Catalog with Wind-Dependent Track Transitions (WHITS)

arXiv:2605.20494v1 Announce Type: new Abstract: Reliable assessment of tropical cyclone (TC) risk is limited by the brevity and spatial sparsity of the historical record, particularly for the rare, hi

safetyarxiv-cs-lg

A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation

arXiv:2605.21058v1 Announce Type: new Abstract: Causal representation learning (CRL) and traditional representation learning have largely developed along different trajectories. Traditional representa

A Systematic Comparison between Extractive Self-Explanations and Human Rationales in Text Classification

arXiv:2410.03296v4 Announce Type: replace Abstract: Instruction-tuned LLMs are able to provide extit{an} explanation about their output to users by generating self-explanations, without requiring the

Advanced Scientific Methodology Plays Rossini

arXiv:2605.20220v1 Announce Type: cross Abstract: A musical score provides the essential instructions for its performance while containing indications - at times implicit - regarding the composer's in

Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling

arXiv:2605.21470v1 Announce Type: new Abstract: Computer-use agents (CUA) automate tasks specified with natural language such as 'order the cheapest item from Taco Bell' by generating sequences of cal

agentsarxiv-cs-lg

AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction

arXiv:2305.09620v4 Announce Type: replace Abstract: Nationally representative surveys track public opinion, yet they ask only a limited set of questions each year, limiting its potential to capture hi

researcharxiv-cs-cl

AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing

arXiv:2605.21421v1 Announce Type: new Abstract: Motion capture is the gold standard for measuring human movement, but clinical use remains limited by cost, technical complexity, and privacy concerns.

local-aiarxiv-cs-cv

Tools

[AINews] OpenAI GPT-next disproves 80 year old Erdős planar unit distance problem for under $1000

OpenAI's GPT-next model reportedly resolved the Erdős planar unit distance problem, a mathematical conjecture that had remained open for approximately 80 years, at a computational cost under $1000. Th

toolslatent-space

Batched Single-Index Global Multi-Armed Bandits with Covariates

model-releasesarxiv-cs-lg

arXiv:2503.00565v3 Announce Type: replace-cross Abstract: The multi-armed bandits (MAB) framework is a widely used approach for sequential decision-making, where a decision-maker selects an arm in eac

Tutorials

Bayesian Optimization by Kernel Regression and Density-based Exploration

arXiv:2502.06178v5 Announce Type: replace-cross Abstract: Bayesian optimization is highly effective for optimizing expensive-to-evaluate black-box functions, but it faces significant computational cha

tutorialsarxiv-cs-lg

Bayesian Preference Learning for Test-Time Steerable Reward Models

arXiv:2602.08819v2 Announce Type: replace-cross Abstract: Reward models are central to aligning language models with human preferences via reinforcement learning (RL). As RL is increasingly applied to

Tools

btw you can move your side chats any where you like

This post likely describes a feature allowing users to relocate or organize their side conversations (chat panels or sidebars) to different positions within an interface, providing flexibility in how

toolsboris-cherny--x

Building Arabic NLP from the Ground Up: Twenty Years of Lessons, Failures, and Open Problems

arXiv:2605.20786v1 Announce Type: new Abstract: This paper reflects on twenty years of building NLP resources and research infrastructure for Arabic, a language spoken by hundreds of millions yet hist

researcharxiv-cs-cl

C^2FG: Control Classifier-Free Guidance via Score Discrepancy Analysis

arXiv:2603.08155v3 Announce Type: replace Abstract: Classifier-Free Guidance (CFG) is a cornerstone of modern conditional diffusion models, yet its reliance on the fixed or heuristic dynamic guidance

Cluster-Based Generalized Additive Models Informed by Random Fourier Features

model-releasesarxiv-cs-lg

arXiv:2512.19373v3 Announce Type: replace-cross Abstract: In developing data-driven modeling methodologies, there is an ongoing need to reconcile the strong predictive performance of opaque black-box

Color has RGB. Sound has MP3. We just gave smell its own system. Today, we’re announcing Sense1, the first model to map activation across al…

Sense1 is announced as the first model capable of mapping olfactory activation patterns across multiple dimensions, establishing a standardized system for smell comparable to how RGB defines color and

agentsyohei-nakajima--x

ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning

arXiv:2605.20385v1 Announce Type: new Abstract: Recent progress in promptable segmentation has shifted visual perception from object-level localization toward concept-level understanding. However, the

Corrected Integrated Laplace Approximation for Bayesian Inference in Latent Gaussian Models

arXiv:2605.20345v1 Announce Type: cross Abstract: Latent Gaussian models (LGMs) are a popular class of Bayesian hierarchical models that include Gaussian processes, as well as certain spatial models a

Distribution-Aware Reward: Reinforcement Learning over Predictive Distributions for LLM Regression

arXiv:2605.20740v1 Announce Type: cross Abstract: Large language models can predict real-valued quantities from heterogeneous inputs such as text, code, and molecular strings, but most training object

DrugRAG: Enhancing Pharmacy LLM Performance Through A Novel Retrieval-Augmented Generation Pipeline

arXiv:2512.14896v2 Announce Type: replace Abstract: In our study, we evaluated large language model (LLM) performance on pharmacy licensure-style question-answering tasks and developed an external kno

E-ReCON: An Energy- and Resource-Efficient Precision-Configurable Sparse nvCIM Macro for Conventional and Spiking Neural Edge Inference

arXiv:2605.20717v1 Announce Type: cross Abstract: This work presents E-ReCON, a 16 Kb energy and resource-efficient digital compute-in-memory (DCIM) macro based on a compact 3T1R ReRAM bitcell for edg

local-aiarxiv-cs-cv

ECUAS{n}: A family of metrics for principled evaluation of uncertainty-augmented systems

model-releasesarxiv-cs-lg

arXiv:2605.20490v1 Announce Type: cross Abstract: In high-stakes automated decision-making, access to predictive uncertainty is essential for enabling users -- human or downstream systems -- to accept