Search: “deployment”

Graded-Relevance Composed Multimodal Retrieval for E-commerce Visual Search at Scale

model-releasesarxiv-cs-cv

arXiv:2609.24152v1 Announce Type: cross Abstract: Visual search on large e-commerce catalogs must serve both 'similarity' queries that ask for items resembling an uploaded image and 'modifier' queries

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

H2RBench: A Real-to-Sim Benchmark for Evaluating Human-to-Robot Transfer

DGX agent

arXiv:2609.24778v1 Announce Type: new Abstract: Learning robot manipulation policies from human video demonstrations constitutes a promising avenue for scalable robot learning. However, comparing diff

model-releasesarxiv-cs-ro

22 Sept 2026

HapticWAM: Distilling Imagined Touch into a World-Action Model without Inference-Time Tactile Sensing

arXiv:2609.23888v1 Announce Type: new Abstract: Contact-rich manipulation requires estimating forces, slip and contact geometry that can remain ambiguous in scene images. Optical tactile sensors provi

HFEMCNet: A Compact Hybrid Frequency Enriched Multi Channel Network for Automatic Modulation Classification

arXiv:2609.22139v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) of received radio signals is prudent for further signal processing tasks such as communication monitoring, c

Hierarchical Aggregation of Semantic Uncertainty in 3D Scene Graphs

arXiv:2609.22351v1 Announce Type: new Abstract: Open-vocabulary 3D Scene Graphs (3DSGs) ground each object node in a vision-language embedding, yet they record every entry as equally certain, so a rob

researcharxiv-cs-cv

HIGenNTO: Scalable Humanoid Interaction Generation via Noise-Space Trajectory Optimization

arXiv:2609.22611v1 Announce Type: new Abstract: Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions rema

agentsarxiv-cs-ro

High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability

arXiv:2609.24278v1 Announce Type: new Abstract: Change point detection (CPD) identifies abrupt and significant changes in sequential data, with applications in human activity recognition, financial ma

agentsarxiv-cs-lg

Applications

IDProxy: CTR Prediction with Multimodal LLMs for Cold-Start Recommendation at Xiaohongshu

arXiv:2603.01590v2 Announce Type: replace-cross Abstract: Content-driven platforms such as Xiaohongshu often leverage click-through rate (CTR) prediction models for recommendation. However, these mode

applicationsarxiv-cs-lg

Learning Beyond What Humans Can Demonstrate

arXiv:2609.24996v1 Announce Type: new Abstract: Behavior cloning for robot manipulation relies on expert demonstrations. However, for tasks that require dynamic stability, precise contact timing, or d

Learning Energy-Efficient Air--Ground Actuation for Hybrid Robots on Stair-Like Terrain

arXiv:2603.26687v2 Announce Type: replace Abstract: Hybrid aerial--ground robots can use thrust to cross obstacles that impede wheel-driven motion, but deciding how much thrust to apply during contact

Learning tactile perception from high-bandwidth single-point sensing

arXiv:2609.24621v1 Announce Type: cross Abstract: Tactile sensing is increasingly being incorporated into learning-based robotic manipulation, yet many existing approaches rely on spatially distribute

Leveraging Industrial Foundation Models at the Edge of Particle Physics Detectors via Distillation Learning and Hardware Co-design

arXiv:2609.23385v1 Announce Type: cross Abstract: Data acquisition (DAQ) systems at future particle physics experiments stand to benefit from the extremes of AI/ML development: large-scale foundation

Leveraging Inference-Time Compute for Diffusion Models via Global Scheduling of Denoising Trajectories

arXiv:2609.22867v1 Announce Type: new Abstract: Diffusion models generate a sample by traversing a denoising trajectory, a sequence of stochastic noise-reduction steps that transforms pure noise into

LG-HCC: Local Geometry-Aware Hierarchical Context Compression for 3D Gaussian Splatting

arXiv:2603.28431v4 Announce Type: replace Abstract: Although 3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, its prohibitive storage overhead severely hinders practical deploym

researcharxiv-cs-cv

LiAuto-MindViT: A Hybrid Vision Backbone with Adaptive Bidirectional Mamba

arXiv:2609.24337v1 Announce Type: new Abstract: While Mamba-based models have shown strong potential for long sequence modeling, adapting them to vision is challenging due to the requirement of local

local-aiarxiv-cs-cv

LLMs Anchor on Chief Complaint and Fail to Integrate Evidence in Sequential Clinical Triage

arXiv:2609.22904v1 Announce Type: new Abstract: Triage in the emergency department (ED) is a sequential decision process that unfolds turn by turn. Existing evaluations of large language models (LLMs)

researcharxiv-cs-cl

Look Before You Steer: Geometry Predicts SAE Feature Steerability

arXiv:2609.22782v1 Announce Type: new Abstract: Steering with SAE features requires per-feature coefficient tuning, which currently demands intervention sweeps. We ask whether properties of the SAE it

LoRA-generating hypernetworks for efficient on-device LLM generative personalization

arXiv:2609.24979v1 Announce Type: new Abstract: On-device large language models (`LLMs'), e.g. running on mobile phones, are ripe for improvement via personalization. The limited compute resources of

Low-Rank Frequency Convolution and Noise-Range Augmentation for Real-Time Pitch Estimation on Edge Devices

arXiv:2609.23340v1 Announce Type: cross Abstract: Pitch estimation on an edge device is constrained in three ways at once. The model must be small, it must stay accurate when the input is noisy, and o

Hardware

Mask-Aware Execution for Efficient JEPA Training

arXiv:2609.22674v1 Announce Type: cross Abstract: Joint Embedding Predictive Architectures (JEPAs) are becoming a core representation-learning primitive and a building block for latent world models ac

hardwarearxiv-cs-lg

MCP-GRANITE Benchmark: GRANularity Interface TEsting for MCP-Based LLM Agents

arXiv:2609.24161v1 Announce Type: cross Abstract: As LLM agents increasingly interact with external tools through standardized protocols such as MCP, tool-interface design becomes a critical yet under

MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback

arXiv:2606.12916v2 Announce Type: replace-cross Abstract: Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle

agentsarxiv-cs-cl

ME-VLM:A Unified VLM for Embodied Cognition and Agent Coordination

arXiv:2609.24526v1 Announce Type: new Abstract: Physical AI requires models to ground visual and linguistic understanding in real-world environments while accounting for environmental constraints and

local-aiarxiv-cs-cv

Measuring Behavioural Signatures of Large Language Models through Psychometric Profiling

arXiv:2609.22934v1 Announce Type: new Abstract: Large language models (LLMs) increasingly mediate human decisions and communication, yet their behavioural regularities remain difficult to characterize

safetyarxiv-cs-cl

MECAIL: Communication-Aware Incremental Learning for Object Detection with 14.6 KB Spatiotemporal Experts

model-releasesarxiv-cs-cv

arXiv:2609.24455v1 Announce Type: new Abstract: Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. However,

Tutorials

Metadata Supervised Imaging Representations for Modelling and Controlling Acquisition Variability

arXiv:2607.11295v2 Announce Type: replace Abstract: Biomedical imaging data exhibit substantial acquisition variability, where identical biological structures can appear markedly different due to diff

tutorialsarxiv-cs-cv

MimicAgent: Quadruped Skills via Prompt-to-Trajectory Generation

model-releasesarxiv-cs-ro

arXiv:2609.24145v1 Announce Type: new Abstract: We present MimicAgent, a prompt-to-trajectory generation framework for learning dynamic quadruped skills. Although reward shaping is extensively used wh

MoE-ACT: Scaling Multi-Task Bimanual Manipulation with Sparse Task-Conditioned Mixture-of-Experts Transformers

model-releasesarxiv-cs-ro

arXiv:2603.15265v2 Announce Type: replace Abstract: Developing a unified policy for multi-task robotic manipulation remains challenging due to policy degradation from task interference and negative tr

Monitorable Chart Reasoning Agents via Verifiable Process Rewards

model-releasesarxiv-cs-cv

arXiv:2609.24071v1 Announce Type: new Abstract: Chart reasoning agents are increasingly used to extract actionable insights in critical domains, achieving state-of-the-art performance on multiple benc

Monocultural Biases: Correlated biases in large language models lead to unequal systemic exclusion rates in hiring

arXiv:2609.22169v1 Announce Type: new Abstract: Employers are increasingly using large language models (LLMs) to automate their hiring process. This paper investigates the risk of monocultural biases,

researcharxiv-cs-cl

Offline Reinforcement Learning for Distribution-Grid Protection

arXiv:2609.24703v1 Announce Type: cross Abstract: Data-driven protection may complement conventional relays in distribution grids whose operating conditions vary with distributed generation, switching

agentsarxiv-cs-lg

On the Efficiency-Safety Dilemma in Large Reasoning Models

arXiv:2609.23587v1 Announce Type: new Abstract: Large reasoning models (LRMs) incur high inference costs, often mitigated by efficiency techniques like quantization and pruning. However, the impact of

safetyarxiv-cs-cl

One to More, More to One: Category-Aware Iterative Expert Training for Software Engineering Agents

arXiv:2609.23377v1 Announce Type: cross Abstract: Repository-level software engineering (SWE) comprises heterogeneous task categories, whose progress under pooled agentic reinforcement learning can be

safetyarxiv-cs-cl

ORDER: A Fictitious-World Benchmark for Domain-Adaptive Embodied AI

model-releasesarxiv-cs-ro

arXiv:2609.22285v1 Announce Type: new Abstract: Adapting language models to new domains via continual pre-training raises a basic evaluation problem: if the training corpus overlaps with what the mode

Orientation-Aware Control and Trajectory Design for Aerial RIS-Assisted Wireless Communications

arXiv:2609.23157v1 Announce Type: cross Abstract: Aerial Reconfigurable Intelligent Surfaces (ARISs) can enhance wireless connectivity in obstructed environments by combining reconfigurable metasurfac

researcharxiv-cs-ro

Perplexity Cost Understates What Activation Quantisation Breaks

arXiv:2609.23125v1 Announce Type: new Abstract: Activation quantisation is usually evaluated with an aggregate metric, perplexity, averaged over every token a model predicts. We ask whether that avera

Pharmacokinetic State Space Models for Unbiased Prediction of Haemodynamic Collapse

arXiv:2609.24338v1 Announce Type: new Abstract: An Intraoperative Hypotension (IOH) event is a frequent complication during administration of general anaesthesia with serious downstream consequences,

local-aiarxiv-cs-lg

PileBelief: Persistent Physical State for Interaction-Driven World Modeling

arXiv:2609.22858v1 Announce Type: new Abstract: World models allow robots to anticipate action consequences before execution. This capability is especially valuable in excavation, where each scoop res

local-aiarxiv-cs-ro

PredActor: Predictive Action Diffusion for Steerable Onboard Humanoid Control

arXiv:2609.24840v1 Announce Type: cross Abstract: Diffusion models offer flexible motion generation, but translating this flexibility into feedback-responsive humanoid control remains challenging. Hie

Predicting Out-of-Distribution Generalization of Neural Operators via Observable Spectral Error Decomposition

arXiv:2609.23529v1 Announce Type: new Abstract: Neural operators have emerged as powerful surrogates for solving partial differential equations (PDEs), yet their reliability under distribution shift r

Predictors and Orchestrators: Parsimonious Machine Learning within an Agentic AI Harness for Multi-Horizon Karst Aquifer Forecasting

arXiv:2609.22251v1 Announce Type: new Abstract: Forecasting karst aquifer dynamics is difficult because recharge responses are nonlinear, event-driven, and governed by strongly heterogeneous flow path

Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models

arXiv:2609.24422v1 Announce Type: new Abstract: Hierarchical data is ubiquitous in the empirical sciences and is most commonly analyzed with generalized linear mixed-effects models (GLMMs). Bayesian i

Probabilistic Scene Graphs: Hierarchical Representation and Real-time System

arXiv:2609.23144v1 Announce Type: new Abstract: 3D scene graphs provide semantically rich and hierarchical representations for robot perception. However, existing systems do not maintain uncertainty a

Applications

RAILS: Retrieval-Augmented Incremental LLM Clustering at Scale

arXiv:2609.24464v1 Announce Type: new Abstract: Using a Large Language Model (LLM) as the clusterer at production scale is hard: prompts cannot hold the entire label space, and per-document serial pro

applicationsarxiv-cs-lg

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

arXiv:2607.14293v2 Announce Type: replace-cross Abstract: Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge ju

Real-Time Plasma State Prediction via FPGA-Accelerated Quantized Recurrent Probabilistic Neural Networks

arXiv:2609.23141v1 Announce Type: cross Abstract: Real time plasma state estimation for control of Tokamak devices are challenging due to the stringent latency requirements of the plasma control syste

Rebekah 1.8b now available

🚀 THE EDGE AI FAMILY HAS ARRIVED. Today we’re opening the doors to a new generation of open-source and open-weight edge AI models from Next GenAi. Meet Rebekah AI 1.8B. 🧠⚡ Small enough to run at the e

local-air-ollama

Applications

Re:CAP - Auditing Retrieval Coverage in Production RAG Pipelines

arXiv:2609.24122v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is hard to monitor in production: exhaustive relevance labels do not exist for non-stationary multi-million-passage

applicationsarxiv-cs-cl