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KnowDemo: Knowledge-Guided Robot Demonstration Generation from Human Videos

arXiv:2609.21229v1 Announce Type: cross Abstract: Learning robot manipulation policies typically requires substantial demonstration data, which are costly to collect on real robots. Recent methods gen

safetyarxiv-cs-ai

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Knowledge-Graph-Augmented Chronos-2 for HEC-RAS Surrogate Forecasting

DGX agent

arXiv:2609.21381v1 Announce Type: cross Abstract: We investigate whether coupling a time-series foundation model to hydraulic project knowledge improves surrogate forecasting of HEC-RAS water-surface

model-releasesarxiv-cs-ai

21 Sept 2026

lambda-Controlled GRPO: Turning Flow-Matching Ratio Instability into a Budgeted Resource

arXiv:2609.22041v1 Announce Type: new Abstract: Reinforcement learning is increasingly used to align image generators with reward signals, and Flow-GRPO recently extended this paradigm to flow-matchin

safetyarxiv-cs-lg

Layerwise Decoupling for Stable Structured Sparsification of Fully Connected Layers

arXiv:2609.21126v1 Announce Type: new Abstract: We propose a decoupled, layerwise method for structurally sparsifying the fully connected layers of pretrained neural networks. Rather than penalizing a

Local Ai

Learned Parametric Emotion Editing: Real-Time Affective Filtering for On-Device Social Media Video

arXiv:2609.21624v1 Announce Type: new Abstract: Problematic internet use affects a growing share of the population, yet common interventions, e.g., time limits, blocking, forced breaks, are coercive a

local-aiarxiv-cs-cv

Learning Cardiac Features: ECG Biometrics Across Time and~Exercise

arXiv:2609.21962v1 Announce Type: new Abstract: Electrocardiograms (ECGs) carry subject-specific patterns enabling reliable individual discrimination, forming the basis of ECG biometrics. Beyond authe

Learning Distance-Conditioned Object Transport for Humanoid Loco-Manipulation from a Single Motion Clip

arXiv:2609.21467v1 Announce Type: new Abstract: Motion tracking can reproduce humanoid loco-manipulation from a single retargeted motion clip, but a policy trained on a fixed reference primarily repro

Learning End-to-End Control for Omnidirectional Aerial Motion on Overactuated Tilt-rotor Quadrotors

arXiv:2602.21583v2 Announce Type: replace Abstract: While reinforcement learning (RL) has been successfully applied to conventional quadrotors for agile and robust flight, whether actuator-level RL ca

Learning Scene-Aware Humanoid Locomotion through 3D Clutter from Immersive Human Demonstrations

arXiv:2609.21107v1 Announce Type: new Abstract: While learning from human motions has enabled highly dynamic humanoid skills such as dancing and martial arts in obstacle-free space, traversal through

Learning Surrogate LPV State-Space Models with Uncertainty Quantification

model-releasesarxiv-cs-lg

arXiv:2603.29532v2 Announce Type: replace-cross Abstract: The Linear Parameter-Varying (LPV) framework enables the construction of surrogate models of complex nonlinear and high-dimensional systems, f

Learning to Move Cities: Deep Meta-Models and Reinforcement Policies for Calibration and Control in Urban Networks

model-releasesarxiv-cs-lg

arXiv:2609.21945v1 Announce Type: new Abstract: Urban transportation networks present complex optimization challenges spanning calibration of high-fidelity simulators and real-time operational control

Learning-to-Optimize as the Missing Architectural Layer of AI-Native Networks

arXiv:2609.21519v1 Announce Type: new Abstract: Artificial Intelligence (AI) is becoming a fundamental design principle of future AI-native communication networks, enabling autonomous resource managem

agentsarxiv-cs-ai

LEGIT: Credentialing Protocol for Trustworthy AI Agent Marketplaces

model-releasesarxiv-cs-ai

arXiv:2609.21325v1 Announce Type: new Abstract: Agentic marketplaces are emerging where AI agents with varying capabilities autonomously complete specialized tasks for buyers. A major challenge of suc

LEMCA: LLM-Guided Synthesis of Efficient Mode-Switching Control Architectures

arXiv:2609.21319v1 Announce Type: new Abstract: Physical control tasks in the natural world, such as driving or object manipulation, frequently exhibit dramatic variations in sensory and compute compl

LIMBO: Learning and Internalizing Model-Free Barrier Objectives for Agile and Safe Whole-Body Control

arXiv:2609.22075v1 Announce Type: new Abstract: Safe whole-body control requires coordinating collision avoidance and balance under high-dimensional, nonlinear dynamics--making safety certificates dif

Listen Before You Speak: Response Planning from Listener Facial Reactions for Conversational Speech Generation

arXiv:2609.21683v1 Announce Type: new Abstract: Conversational speech depends on dialogue context and the listener's immediately preceding behavior. We propose ReACT-TTS, a two-stage framework that us

LLM-Generated Feature Pools for Time Series Anomaly Detection

arXiv:2609.21801v1 Announce Type: new Abstract: We study how far a simple statistical pipeline can go on univariate time series anomaly detection under a strict selection protocol. The method extracts

LLMs as Feature Engineers for Text-and-Tabular Prediction

arXiv:2609.21894v1 Announce Type: new Abstract: We introduce an iterative framework that automates the extraction of interpretable, schema-bound categorical features from unstructured text for tabular

LogicTrack: Auditing Reasoning Trajectories of Large Language Models with Formal Logic Solvers

arXiv:2609.21492v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning has been shown to improve the performance of large language models (LLMs), yet existing optimization methods largely re

LOInK: Learned Optimal Inverse Kinematics via Structured Neural Surrogate Models

arXiv:2609.21275v1 Announce Type: new Abstract: We introduce Learned Optimal Inverse Kinematics (LOInK), a method to generate approximately optimal solutions to an inverse kinematics problem. When tra

LoRA Enhanced Contrastive Learning with SAS Vision Transformers

model-releasesarxiv-cs-ai

arXiv:2609.21061v1 Announce Type: new Abstract: Automatic target recognition (ATR) with synthetic aperture sonar (SAS) supports advanced naval capabilities, but deep learning is constrained by scarce

LunaDrive: A Delay-Compensated High-Voltage GaN FET-Based Motor Driver for Dynamic Robots with Flat BLDC Motors

arXiv:2609.21818v1 Announce Type: new Abstract: The performance improvement of high-power flat BLDC motors has accelerated the development of dynamic robots. However, many commercially available servo

M2G-LLM: Enhancing Clinical Prediction via Multimodal Graph Reasoning and LLM Context Injection

arXiv:2609.21164v1 Announce Type: new Abstract: Integrating diverse data modalities --- such as clinical notes, laboratory results, and medical imaging --- is essential for advancing clinical decision

safetyarxiv-cs-lg

MA-LIPP: Cooperative Multi-Agent Load-Aware Informative Path Planning for Heterogeneous Robot Teams

arXiv:2609.21167v1 Announce Type: new Abstract: Field robotics missions often require physical samples to be returned to laboratories for analysis, making path planning inherently load-aware and order

agentsarxiv-cs-ro

MAAP: Multi-Agent Active Perception for Collaborative Manipulation

arXiv:2609.21929v1 Announce Type: new Abstract: Multi-agent manipulation naturally produces multiple task-driven viewpoints: every arm carries a wrist camera and moves through the scene while acting.

agentsarxiv-cs-ro

MACE: Memory-Agent Co-Evolution with Adaptive Memory Graphs for Multi-Agent Systems

arXiv:2609.21533v1 Announce Type: new Abstract: LLM-based multi-agent systems generate collaboration traces that record how agents plan tasks, verify intermediate results, and repair failures. Reusing

agentsarxiv-cs-lg

MAGIC: Marginal-Guided Compression with Optimal Transport for Efficient Visual Document Retrieval

arXiv:2609.21018v1 Announce Type: new Abstract: Recent visual document retrieval (VDR) systems such as ColPali use multi-vector page embeddings, in which patch-level vectors enable fine-grained eviden

researcharxiv-cs-cv

MAPLE-RF: Efficient Probabilistic RF Source Localization in Partially Explored Environments

model-releasesarxiv-cs-ro

arXiv:2609.21026v1 Announce Type: new Abstract: Localizing a radio-frequency (RF) transmitter from received signals often requires a model of the environment to predict how obstacles block and reflect

MarineCraft: Enabling Rapid Prototyping of Underwater Robots via Modular Construction

arXiv:2609.21396v1 Announce Type: new Abstract: Underwater robot development is often hindered by the complexities of waterproofing and wiring, which significantly delay the rapid prototyping process.

Local Ai

MarsFM: Shading-Regularized Flow Matching for Martian Relief Estimation

arXiv:2609.21095v1 Announce Type: new Abstract: We present MarsFM, an image-conditioned latent flow-matching model for local Martian relief estimation from single-band HiRISE RED orthoimagery. The met

local-aiarxiv-cs-cv

Matrix AdaGrad: Row-wise and Column-wise Adaptive Subgradient Methods

arXiv:2609.21815v1 Announce Type: cross Abstract: Adaptive optimization methods such as AdaGrad and Adam are widely used in modern neural-network training, but their adaptive scaling is primarily desi

ME-Dex 1.0: Bringing Heterogeneous Tactile Sensing into World Action Modeling

arXiv:2609.21449v1 Announce Type: new Abstract: World Action Models bring the predictive capabilities of video models into robot action generation, providing a rich foundation for modeling future visu

agentsarxiv-cs-cv

Measuring Digital Labour Market Transitions with a Digital Semantic Score: An AI-Based Methodology Applied to the Dutch Labour Market

arXiv:2608.24222v2 Announce Type: replace Abstract: The digital transformation of the Dutch labour market is reshaping occupational language, career pathways, and job-related skills. Addressing these

researcharxiv-cs-cl

Tutorials

MemeTAG: Keyword-Driven Meme Classification through Tag Embedding Reconstruction

arXiv:2609.20962v1 Announce Type: new Abstract: The proliferation of harmful internet memes poses a significant societal threat, yet their automated classification remains a formidable algorithmic cha

tutorialsarxiv-cs-cv

MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks

model-releasesarxiv-cs-cl

arXiv:2602.16313v2 Announce Type: replace Abstract: Existing evaluations of agents with memory typically assess memorization and action in isolation. One class of benchmarks evaluates memorization by

MENASpeechBank: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs

arXiv:2602.07036v2 Announce Type: replace-cross Abstract: Audio large language models (AudioLLMs) enable instruction following over speech and general audio, but progress is limited by the scarcity of

agentsarxiv-cs-ai

MetaPusher: Meta Learning and Planning for Nonprehensile Manipulation of Unseen Objects with Rapid Online Adaption

arXiv:2609.21122v1 Announce Type: new Abstract: Manipulating previously unseen objects remains challenging, as their dynamics depend on latent physical properties, such as friction and mass distributi

Local Ai

Micro-Collaborative Poisoning: A Distributed Attack on RAG Systems

arXiv:2609.21573v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves large language models by grounding outputs in external knowledge sources, but this dependency also creat

local-aiarxiv-cs-ai

MicroHookACT: Monocular Microscopic Vision Guided Visuomotor Policy for Flexible Microelectrode Hooking

arXiv:2609.21365v1 Announce Type: new Abstract: Automated needle-loop hooking is a critical step in flexible microelectrode (FME) implantation. This paper presents MicroHookACT, an imitation learning-

MintAct: A Unified Visual Agent for Digital Environments

arXiv:2609.22083v1 Announce Type: new Abstract: We present MintAct, a family of vision-language models that unifies UI grounding, multi-step navigation across mobile, desktop, and web, and visual tool

safetyarxiv-cs-cv

MIRAGE: Multi-Perspective Creative Language Model Reasoning with Reinforcement Learning Guidance

arXiv:2609.21554v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have revolutionized artificial intelligence and how human interact with AIs. Despite impressive advancem

agentsarxiv-cs-cl

MIRCID: Inferred Hub-miRNAs Drive Cross-Task Improvements in Drug Mechanistic Modeling

arXiv:2609.21280v1 Announce Type: new Abstract: Drug mechanism-of-action (MoA) modeling commonly relies on perturbational transcriptomes, but matched microRNA (miRNA) measurements are often unavailabl

MIST: Multimodal Survival Prediction with Genomic-Guided Histology Attention

arXiv:2609.21811v1 Announce Type: new Abstract: Multimodal survival models can combine complementary prognostic information from whole-slide images and genomic profiles, but effective fusion remains c

safetyarxiv-cs-ai

MME-Safety: A Fine-grained Benchmark for Safety Evaluation of MLLMs

model-releasesarxiv-cs-cl

arXiv:2609.20850v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) show remarkable advancements, their cross-modal capabilities introduce complex vulnerabilities that easil

Moral Entropy: Auditing Bias and Uncertainty in Moral Judgment

arXiv:2609.21992v1 Announce Type: new Abstract: Most work in computational ethics treats annotator disagreement on moral content as noise to be voted away, collapsed into majority vote or the more per

safetyarxiv-cs-cl

Tutorials

Morphology-Aware Ambiguity Learning for Wafer Defect Decision Support

arXiv:2609.21866v1 Announce Type: new Abstract: Wafer map defect recognition is commonly formulated as a fixed-taxonomy classification problem that assigns each wafer to a single defect class. However

tutorialsarxiv-cs-cv

MOSAIC-SR: Transformer-Guided Symbolic Regression for Scientific Equation Recovery

arXiv:2609.20997v1 Announce Type: new Abstract: Symbolic regression aims to recover closed-form equations from observations, providing interpretable models for scientific discovery. Existing approache

MT-WAM: Reorienting the One-Pass Predictive Representation Toward Action Generation

arXiv:2609.21474v1 Announce Type: new Abstract: Fast-WAM shows that video-action co-training improves control without generating future video at inference, making the representation from a single vide

safetyarxiv-cs-cv