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arXiv:2406.04814v4 Announce Type: replace-cross Abstract: Video diffusion models can enable embodied agents to anticipate plausible futures from the recent past, but they are typically trained offline

tutorialsarxiv-cs-lg

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Human DGX agent

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Research

LiFR v2: Completion-Augmented Event Propagation for High-Rate Dense Prediction

DGX agent

arXiv:2609.25803v2 Announce Type: new Abstract: High-rate dense perception in dynamic environments is limited by the low update rate of RGB cameras, as rapid scene changes can occur between frames. Ev

researcharxiv-cs-cv

23 Sept 2026

Lightweight Ranking Heads: Accelerating Multi-Task Experimentation in Production Recommender Systems

arXiv:2609.25433v1 Announce Type: new Abstract: Modern production-scale recommender systems rely on complex, multi-task ranking models. Introducing new prediction tasks into these massive systems ofte

applicationsarxiv-cs-lg

LIMIT: Less Is More for Instruction Tuning in Text-to-SQL

model-releasesarxiv-cs-ai

arXiv:2609.24186v1 Announce Type: new Abstract: Large language models have achieved remarkable progress on Text-to-SQL through reasoning-enhanced fine-tuning, yet existing approaches predominantly rel

Linear probing enables Ship-Radiated Noise recognition with pretrained audio embeddings

arXiv:2601.08358v2 Announce Type: replace Abstract: Even though the ocean covers the majority of the planet's surface, it remains the least explored ecosystem. As light and radio waves do not propagat

Listen Then Reason: Perception-Grounded Test-Time Reinforcement Learning for Large Audio-Language Models

arXiv:2609.23589v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are increasingly used for a broader range of audio reasoning tasks. These models typically incorporate audio repre

researcharxiv-cs-ai

LLaVA-Assessor: Building the Foundation LMM For Visual Quality Assessment

arXiv:2609.26205v1 Announce Type: new Abstract: Aligning with the human visual system~(HVS) in perceiving and evaluating the quality of visual signals is a central objective of machine-vision-based vi

Local Ai

LLM-Driven Training-free Location-Attribute Synergic Fusion: A Closed-Loop Paradigm for Dual-source Encrypted POIs and LULC Mapping

arXiv:2609.25051v1 Announce Type: new Abstract: Dual-source encrypted points of interest (DSEP), POIs from two encrypted coordinate systems, suffer from intertwined location and attribute uncertaintie

local-aiarxiv-cs-cl

Longitudinal Retinal Vascular Remodeling in Myopic Children Treated with Orthokeratology or Defocus Lenses: A Two-Year Comparative Study

arXiv:2609.26662v1 Announce Type: new Abstract: Purposes: To characterize longitudinal retinal vascular changes in myopic children treated with orthokeratology (OK) or multifocal defocus lenses (Defoc

LoRango: It Takes Two LoRAs to Unlock Hidden Behaviors in Diffusion Models

arXiv:2609.25884v1 Announce Type: cross Abstract: Users commonly combine multiple Low-Rank Adaptation (LoRA) adapters to personalize images with different subjects, styles, and visual attributes. Yet

safetyarxiv-cs-cv

Low-Rank Attention Residuals

arXiv:2607.09694v2 Announce Type: replace-cross Abstract: Attention Residuals (AttnRes) replace the fixed residual sum with depth-wise attention over previous sub-layer outputs in Large Language Model

researcharxiv-cs-cl

MachEmbodied-U0: Unified Understanding and Generation Model for Embodied Intelligence

model-releasesarxiv-cs-ro

arXiv:2609.25627v1 Announce Type: new Abstract: General-purpose robot control requires models to understand task intent, identify where to interact, capture how the scene evolves, and generate precise

Local Ai

MAGIC: Mixed-Granularity Agent Graphs via Incremental Construction with Dense-Reward Reinforcement Learning

arXiv:2609.26667v1 Announce Type: new Abstract: Collaboration topology shapes both the performance and execution cost of LLM-based multi-agent systems. Because tasks differ in complexity and required

local-aiarxiv-cs-lg

Magnitude Profile Pruning: Calibration-Free Structured Attention Head Removal for Transformer Compression

arXiv:2609.26177v1 Announce Type: new Abstract: Structured pruning of attention heads provides a hardware-friendly way to compress Transformer language models. However, existing methods for measuring

Mammo-LIFE: Longitudinal Mammographic Imaging and Clinical Feature Enrichment for Post-Radiotherapy Outcome Prediction

arXiv:2609.26443v1 Announce Type: new Abstract: Recent advances in Artificial Intelligence (AI)-powered Computer-Aided Diagnosis (CAD) systems have substantially improved breast cancer screening, diag

Manipulation of Deformable Linear Objects Using Model Predictive Path Integral Control with Bidirectional Long Short-Term Memory Learning

arXiv:2609.26238v1 Announce Type: new Abstract: The manipulation of Deformable Linear Objects (DLOs) such as cables poses a significant challenge for automation due to their infinite degrees of freedo

researcharxiv-cs-ro

Manipulation with Stability Guarantees: Linear Deformable Objects with Non-negligible Physical Response Grasped at Multiple Location

arXiv:2609.26004v1 Announce Type: new Abstract: Most research on the manipulation of deformable objects focuses on lightweight systems with negligible mechanical response, effectively restricting atte

researcharxiv-cs-ro

Margin-Drop Coordinates for Cross-Budget Robustness Evaluation

arXiv:2609.26081v1 Announce Type: new Abstract: Fixed-budget robustness evaluation can select the wrong frozen vision encoder. An encoder that survives a shallow attack may lose most of that robustnes

Marginal Log-Likelihood Increments under Dirichlet-Smoothed Markov Estimation

arXiv:2609.25675v1 Announce Type: new Abstract: For a Dirichlet-smoothed transition model, the effect of adding one workflow trace to the training archive is an exact change in reference-weighted log

applicationsarxiv-cs-lg

Match One, Learn with Graph: One-to-Graph Query Collaboration with Backward Sharing for Object Detection

model-releasesarxiv-cs-cv

arXiv:2609.26092v1 Announce Type: new Abstract: One-to-one (O2O) matching enables Detection Transformers (DETRs) to perform end-to-end set prediction by assigning each object to a single positive quer

MatcherCompass: A Deployment-Aware Benchmark to Guide Image Matcher Selection in the Wild

model-releasesarxiv-cs-ro

arXiv:2609.25688v1 Announce Type: new Abstract: Field robots operating across time of day and sensing modalities require accurate image correspondences within onboard time and resource budgets. Howeve

MatchFusion: Explicit-Implicit Instance Matching for Spatio-Temporal Multimodal Autonomous Driving

arXiv:2609.25860v1 Announce Type: cross Abstract: Sparse instance representations provide a compact interface for spatial LiDAR-camera and temporal past-current interaction in multimodal perception an

MATE: Multi-Agent Virtual Teleoperation Platform for Humanoid Collaboration Data Collection

arXiv:2609.26520v1 Announce Type: new Abstract: Humanoid robots require diverse embodied experiences to acquire complex loco-manipulation and collaborative skills. However, existing humanoid data pipe

MATE: Policy-Aware Security Auditing for Mobile Agents via Synthesis-Driven Trajectory Learning

model-releasesarxiv-cs-ai

arXiv:2609.22724v1 Announce Type: cross Abstract: Mobile agents powered by foundation models now automate complex, multi-step workflows on real devices, but their trajectories can violate app-specific

MATES: Learning Multi-Agent Interactions by Transforming Observations for Frozen Single-Agent Policies

arXiv:2609.26010v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) commonly trains decentralized policies from scratch, requiring agents to acquire individual task competence

Matryoshka attribution: Learning to attribute language model outputs to representations and weights

arXiv:2609.25518v1 Announce Type: new Abstract: Attributing language model outputs to their internal computations is an open problem in interpretability. Existing methods, which use causal interventio

MAVP: Map-Aware Visuomotor Policies for Mobile Manipulation

arXiv:2609.26378v1 Announce Type: cross Abstract: Successful mobile manipulation requires coordinated base and arm motion while maintaining accurate spatial positioning. However, demonstration-trained

safetyarxiv-cs-lg

Agents

MAWILE: Multi-Axis Workbench for Inspecting LLM Evaluators

arXiv:2609.22599v1 Announce Type: new Abstract: Large language model (LLM) judges provide a flexible and scalable method for evaluating model and agent outputs, but their verdicts can be sensitive to

agentsarxiv-cs-ai

mbariml: a curation pipeline for turning deep-sea imagery and video into object-detection training data

arXiv:2609.25500v1 Announce Type: new Abstract: Training data quantity and quality greatly affect object detection model performance, regardless of model architecture. When using object detection mode

MCPGen: Benchmarking LLMs on Executable MCPWorkflow Development

model-releasesarxiv-cs-ai

arXiv:2609.23925v1 Announce Type: cross Abstract: We study whether LLMs can produce executable workflow artifacts that remain consistent across graph structure, tool implementation, schema bindings, a

Mean Velocity Matching: Rethinking Generative Dynamics in Diffusion Models

arXiv:2609.25444v1 Announce Type: new Abstract: This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

arXiv:2609.26693v1 Announce Type: new Abstract: A coding agent must emit a valid tool call--a parseable invocation of a tool in the provided schema--before the harness can execute its chosen action. W

Agents

'MeBo Leaves a Piece of You Behind': Designing a Relational Voice-Based Memory Companion for Older Adults

arXiv:2609.24706v1 Announce Type: cross Abstract: Autobiographical remembering supports identity, well-being, and social connection in later life, yet voice-based memory technologies largely rely on i

agentsarxiv-cs-ai

MECT: Mixture of Experts with CNN-Transformer Network for Speaker verification

arXiv:2609.24061v1 Announce Type: cross Abstract: In this paper, we propose MECT, a speaker verification model that integrates the Mixture-of-Experts (MoE) mechanism into a CNN-Transformer backbone wi

researcharxiv-cs-ai

MedRSI: Recursive Self-Improvement for Medical Agents via Clinically Aligned Self-Evolution

arXiv:2609.24838v1 Announce Type: new Abstract: Medical agents increasingly combine general reasoning models with specialized clinical tools, yet their capabilities remain largely fixed by what clinic

safetyarxiv-cs-ai

MedVLA: A Hierarchical Vision-Language-Action Framework for Closed-Loop Precision Medical Robot Manipulation

arXiv:2609.25756v1 Announce Type: new Abstract: Precision medical robotics demands adaptive decision-making under strict safety, interpretability, and execution constraints. Although recent Vision-Lan

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range

applicationsarxiv-cs-ai

MemoryAthena: Adaptive Routing over Latent and Generated Memories

arXiv:2609.25853v1 Announce Type: new Abstract: Learned-memory methods store information in an explicit table and consume it through a separate reader, allowing addressing, storage, and reading to be

researcharxiv-cs-cl

Metric-Bench: Exploring In-context Spatial Metric Reasoning in VLMs for Indoor Scenes

model-releasesarxiv-cs-cv

arXiv:2609.25841v1 Announce Type: new Abstract: Metric reasoning is a critical and challenging task for Vision Language Models (VLMs), playing a pivotal role in embodied AI tasks such as robotic manip

MGRL-RSCC: Multi-Granularity Reward Reinforcement Learning for Fine-Grained Remote Sensing Change Captioning

model-releasesarxiv-cs-lg

arXiv:2609.26166v1 Announce Type: cross Abstract: Remote Sensing Change Captioning (RSCC), which aims to generate accurate and detailed linguistic descriptions of ground object variations from bi-temp

MIAR: Medical Image Super-Resolution With Autoregressive Modeling

arXiv:2609.26103v1 Announce Type: new Abstract: Medical Image Super-Resolution (MISR) aims to enhance spatial resolution without requiring hardware modifications. Although deep learning has yielded pr

MICRO: Multi-Fidelity Active Search for Severe Error Discovery

arXiv:2609.26025v1 Announce Type: cross Abstract: Human feedback can vary in cost and informativeness. Strong feedback can reveal severe errors but is costly, so cheaper quality ratings can help decid

researcharxiv-cs-cl

MicroPush: A Lightweight Simulator for Sim-to-Real Microrobotic Pushing and Assembly

arXiv:2602.23607v2 Announce Type: replace Abstract: Developing learning-based autonomy for microrobotic manipulation is difficult because physical trials are slow, variable, and poorly suited to large

MIND the Gap: A Geographic Implicit Neural Representation with Adjustable Spatial Scale

arXiv:2609.25454v1 Announce Type: cross Abstract: Geographic measurements are often sparse, leaving large areas without labels for the quantities we want to map. Geographic implicit neural representat

Tutorials

Minimal Recurrent Behavioral Memory for Imitation under Partial Observability

arXiv:2609.25757v1 Announce Type: new Abstract: What is the least recurrent memory needed to reproduce a specified expert under partial observability? The instantaneous requirement is the conditional

tutorialsarxiv-cs-lg

Mining Legal Arguments in U.S. Corporate Case Law

arXiv:2609.25441v1 Announce Type: new Abstract: Legal argument mining supports passage classification, retrieval, and argument completion. This work introduces an expert-annotated dataset of 42 U.S. f

Mirror Skin: In Situ Visualization of Robot Touch Intent on Robotic Skin

arXiv:2512.11472v3 Announce Type: replace-cross Abstract: Effective communication of robot touch intent is essential for safe and predictable physical human-robot interaction. While intent communicati

applicationsarxiv-cs-ro

MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration

arXiv:2609.25331v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an im- portant component of visual sensing systems operating under degraded illumination, including nighttime surv

safetyarxiv-cs-cv