applications

Build real-time voice streaming applications with Amazon Nova Sonic and WebRTC

Building end-to-end live streaming applications with real-time voice interaction presents several challenges. This post introduces a solution based on Amazon Nova 2 Sonic (Nova Sonic) and Amazon Kines

applicationsaws-ml-blog

Applications

Causal Algorithmic Recourse: Foundations and Methods

DGX agent

arXiv:2605.11373v1 Announce Type: cross Abstract: The trustworthiness of AI decision-making systems is increasingly important. A key feature of such systems is the ability to provide recommendations f

applicationsarxiv-cs-lg

13 May 2026

Celonis buys decision-intelligence startup Ikigai Labs to provide operational context for enterprise AI

Process mining software company Celonis SE said today it has snapped up the Massachusetts Institute of Technology-linked decision intelligence startup Ikigai Labs Inc., planning to use it to power a n

applicationssiliconangle

Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner

arXiv:2510.03206v2 Announce Type: replace-cross Abstract: Diffusion language models, especially masked discrete diffusion models, have achieved great success recently. While there are some theoretical

Concordance Comparison as a Means of Assembling Local Grammars

arXiv:2605.11862v1 Announce Type: new Abstract: Named Entity Recognition for person names is an important but non-trivial task in information extraction. This article uses a tool that compares the con

Config, which is building a data layer for robotics foundation models, raised a 27M seed at a 200M+ valuation led by Samsung Venture Investment (Kate Park/TechCrunch)

Kate Park / TechCrunch: Config, which is building a data layer for robotics foundation models, raised a 27M seed at a 200M+ valuation led by Samsung Venture Investment — Asia's push into physical AI i

applicationstechmeme

Context Steering: A New Paradigm for Compression-based Embeddings by Synthesizing Relevant Information Features

arXiv:2508.14780v2 Announce Type: replace Abstract: Compression-based dissimilarities (CD) offer a flexible and domain-agnostic means of measuring similarity by identifying implicit information throug

Could this be the moment that drug manufacturing takes off in orbit?

Varda Space Industries and United Therapeutics announced a collaboration to conduct pharmaceutical processing of small molecule medicines in orbit, combining Varda's orbital manufacturing platform wit

applicationsars-technica

Data quality is the AI strategy

Data quality is a foundational component of effective AI strategy, as high-quality training and operational data directly impacts model performance, reliability, and business outcomes. The article lik

applicationsdatabricks

Deep Minds and Shallow Probes

arXiv:2605.11448v1 Announce Type: new Abstract: Neural representations are not unique objects. Even when two systems realize the same downstream computation, their hidden coordinates may differ by rep

Delay-Empowered Causal Hierarchical Reinforcement Learning

arXiv:2605.12261v1 Announce Type: new Abstract: Many real-world tasks involve delayed effects, where the outcomes of actions emerge after varying time lags. Existing delay-aware reinforcement learning

Detecting In-Person Conversations in Noisy Real-World Environments with Smartwatch Audio and Motion Sensing

arXiv:2507.12002v2 Announce Type: replace Abstract: Social interactions play a crucial role in shaping human behavior, relationships, and societies. It encompasses various forms of communication, such

DexTwist: Dexterous Hand Retargeting for Twist Motion via Mixed Reality-based Teleoperation

arXiv:2605.12182v1 Announce Type: new Abstract: Dexterous teleoperation via Mixed Reality (MR)-based interfaces offers a scalable paradigm for transferring human manipulation skills to dexterous robot

applicationsarxiv-cs-ro

Does Head Pose Correction Improve Biometric Facial Recognition?

arXiv:2512.03199v2 Announce Type: replace Abstract: Biometric facial recognition models often demonstrate significant decreases in accuracy when processing real-world images, often characterized by po

Dual-Temporal LSTM with Hybrid Attention for Airline Passenger Load Factor Forecasting: Integrating Intra-Flight and Inter-Flight Booking Dynamics

arXiv:2605.11569v1 Announce Type: cross Abstract: Accurate short-term demand forecasting is crucial to airline revenue management, yet most existing systems fail to meet this need because current mode

Dynamic Execution Commitment of Vision-Language-Action Models

arXiv:2605.11567v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models predominantly adopt action chunking, i.e., predicting and committing to a short horizon of consecutive low-level act

ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models

arXiv:2605.10993v1 Announce Type: new Abstract: Memory capacity is a critical factor determining the performance of Vision-Language-Action (VLA) models in long-horizon manipulation tasks. Existing mem

applicationsarxiv-cs-ro

Efficient and provably convergent end-to-end training of deep neural networks with linear constraints

arXiv:2605.11526v1 Announce Type: cross Abstract: Training a deep neural network with the outputs of selected layers satisfying linear constraints is required in many contemporary data-driven applicat

Efficient LLM-based Advertising via Model Compression and Parallel Verification

arXiv:2605.11582v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable potential in advertising scenarios such as ad creative generation and targeted advertising. However,

Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance

arXiv:2605.12453v1 Announce Type: cross Abstract: To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cas

Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentation

arXiv:2605.12198v1 Announce Type: new Abstract: Pedestrian motion, due to its causal nature, is strongly influenced by domain gaps arising from discrepancies between training and testing data distribu

Environment-Adaptive Preference Optimization for Wildfire Prediction

arXiv:2605.12435v1 Announce Type: new Abstract: Predicting rare extreme events such as wildfires from meteorological data requires models that remain reliable under evolving environmental conditions.

Estimating Subgraph Importance with Structural Prior Domain Knowledge

arXiv:2605.12009v1 Announce Type: new Abstract: We propose a subgraph importance estimation method for pretrained Graph Neural Networks (GNNs) on graph-level tasks, formulated as a linear Group Lasso

Fast Image Super-Resolution via Consistency Rectified Flow

arXiv:2605.12377v1 Announce Type: new Abstract: Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step s

Fine, you can do sorcery sometimes. But go all the way: circles of salt, grimoires, robes.

applicationsethan-mollick--x

This post likely discusses a humorous or philosophical take on the conditional acceptance of magical practices, suggesting that if one is going to engage in sorcery, they should commit fully to all th

Fractal Graph Contrastive Learning

arXiv:2505.11356v4 Announce Type: replace Abstract: Graph Contrastive Learning (GCL) relies on semantically consistent graph augmentations, but common local perturbations provide limited control over

From a robot expert https://x.com/mattbeane/status/2054667222040330265?s=20

applicationsethan-mollick--x

From a robot expert https://x.com/mattbeane/status/2054667222040330265?s=20 @emollick It is very impressive. Deformable goods? Reflection issues? Imperfect labels? Impossible problems just a few years

From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction

arXiv:2605.11774v1 Announce Type: new Abstract: By processing electronic health records (EHRs) as natural language sequences, large language models (LLMs) have shown potential in clinical prediction t

HamBR: Active Decision Boundary Restoration Based on Hamiltonian Dynamics for Learning with Noisy Labels

arXiv:2605.11383v1 Announce Type: new Abstract: In large-scale visual recognition and data mining tasks, the presence of noisy labels severely undermines the generalization capability of deep neural n

Hide to See: Reasoning-prefix Masking for Visual-anchored Thinking in VLM Distillation

arXiv:2605.11651v1 Announce Type: cross Abstract: Recent think-answer approaches in VLMs, such as Qwen3-VL-Thinking, boost reasoning performance by leveraging intermediate thinking steps before the fi

Hierarchical Multi-Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation

arXiv:2605.10975v1 Announce Type: new Abstract: Graphs with heterophily, where adjacent nodes carry different labels, are prevalent in real-world applications, from social networks to molecular intera

How the Strait of Hormuz blockade is disrupting global chip supply chains, affecting supplies of helium, bromine, sulfur, and thinners essential to chipmaking (Bloomberg)

Bloomberg: How the Strait of Hormuz blockade is disrupting global chip supply chains, affecting supplies of helium, bromine, sulfur, and thinners essential to chipmaking — Asian chipmakers, including

applicationstechmeme

I don't understand the path forward for Mythos releases. Google & OpenAI will have equivalent models, and they are approaching AI cyber risk…

applicationsethan-mollick--x

I don't understand the path forward for Mythos releases. Google & OpenAI will have equivalent models, and they are approaching AI cyber risk guardrails differently, so they will presumably just releas

IGV-RRT: Prior-Real-Time Observation Fusion for Active Object Search in Changing Environments

arXiv:2603.21887v2 Announce Type: replace Abstract: Object Goal Navigation (ObjectNav) in temporally changing indoor environments is challenging because object relocation can invalidate historical sce

applicationsarxiv-cs-ro

In-context learning to predict critical transitions in dynamical systems

arXiv:2605.12308v1 Announce Type: new Abstract: Critical transitions - abrupt, often irreversible changes in system dynamics - arise across human and natural systems, often with catastrophic consequen

Instruct-ICL: Instruction-Guided In-Context Learning for Post-Disaster Damage Assessment

arXiv:2605.11439v1 Announce Type: new Abstract: Rapid and accurate situational awareness is essential for effective response during natural disasters, where delays in analysis can significantly hinder

Instructions shape Production of Language, not Processing

arXiv:2605.11206v1 Announce Type: new Abstract: Instructions trigger a production-centered mechanism in language models. Through a cognitively inspired lens that separates language processing and prod

Interpretability Can Be Actionable

arXiv:2605.11161v1 Announce Type: new Abstract: Interpretability aims to explain the behavior of deep neural networks. Despite rapid growth, there is mounting concern that much of this work has not tr

Investor docs: Anthropic's revenue run rate is on track to hit $50B by the end of June; Ramp says more of its customers now use Anthropic than OpenAI, a first (Kate Clark/Wall Street Journal)

Kate Clark / Wall Street Journal: Investor docs: Anthropic's revenue run rate is on track to hit $50B by the end of June; Ramp says more of its customers now use Anthropic than OpenAI, a first — After

applicationstechmeme

JupiterOne targets AI sprawl with new attack surface and vulnerability tools

Artificial intelligence risk management platform provider JupiterOne Inc. today announced the launch of two new offerings aimed at helping security teams get a handle on risk created by the sprawl of

applicationssiliconangle

Learning plug-in surrogate endpoints for randomized experiments

arXiv:2605.12051v1 Announce Type: new Abstract: Surrogate endpoints are used in place of long-term outcomes in randomized experiments when observing the real outcome for a large enough cohort is prohi

Localising Dropout Variance in Twin Networks

arXiv:2507.03622v2 Announce Type: replace Abstract: Accurate individual treatment-effect estimation demands not only reliable point predictions but also uncertainty measures that help practitioners lo

M^4-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection

arXiv:2605.11760v1 Announce Type: new Abstract: The Segment Anything Model 2 (SAM2) has emerged as a foundation model for universal segmentation. Owing to its generalizable visual representations, SAM

Make It Long, Keep It Fast: End-to-End 10k-Sequence Modeling at Billion Scale on Douyin Recommendation

arXiv:2511.06077v2 Announce Type: replace Abstract: Short-video recommenders such as Douyin must exploit extremely long user histories without breaking latency or cost budgets. We present an end-to-en

MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification

arXiv:2605.11408v1 Announce Type: cross Abstract: Tabular data forms the backbone of high-stakes decision systems in finance, healthcare, and beyond. Yet industrial tabular datasets are inherently dif

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models

arXiv:2605.02798v1 Announce Type: cross Abstract: We present an experimental study of energy-to-solution (ETS) of hybrid quantum-classical applications, enabled by direct instrumentation of power cons

Mechanistic Interpretability of ASR models using Sparse Autoencoders

arXiv:2605.12225v1 Announce Type: new Abstract: Understanding the internal machinations of deep Transformer-based NLP models is more crucial than ever as these models see widespread use in various dom

Model-Level GNN Explanations via Rule-to-Graph Readout for Logit Reconstruction

arXiv:2503.09051v2 Announce Type: replace Abstract: We propose a novel model-level GNN explanation framework that shifts the explanation target from class-wise rule extraction to rule-based logit reco