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Exploration of Foundation Model-Based Robots in Patient and Elderly Care

arXiv:2606.10208v1 Announce Type: cross Abstract: Demand for older-adult and patient care is growing rapidly as populations age worldwide. Foundation models are increasingly being integrated into robo

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Exploring the Design Space of Reward Backpropagation for Flow Matching

DGX agent

arXiv:2606.11075v1 Announce Type: new Abstract: Aligning text-to-image flow matching models with human preferences via direct reward backpropagation is sample-efficient but hampered by two well-known

researcharxiv-cs-lg

10 Jun 2026

Express Language Modeling

arXiv:2606.10944v1 Announce Type: new Abstract: We introduce a new tool, Express, for converting a non-causal attention approximation into a causal approximation with matching approximation guarantees

FadeMem: Distance-Aware Memory Consolidation for Autoregressive Video Diffusion

arXiv:2606.10671v1 Announce Type: new Abstract: Autoregressive video generators synthesize long videos by generating successive temporal segments, but their historical KV cache grows with video length

FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching

arXiv:2606.10124v1 Announce Type: cross Abstract: Federated learning (FL) is often subject to aggregation variance if clients do not consistently participate in training rounds. While reusing stale mo

Few-step Generative Models as Lossy Compression

arXiv:2606.10450v1 Announce Type: new Abstract: DiffC provides a principled way to reuse pre-trained diffusion models for lossy compression, but its encoding and decoding procedures remain slow becaus

FG-Attn: Leveraging Fine-Grained Sparse Attention in Video Diffusion Models

arXiv:2509.16518v2 Announce Type: replace Abstract: Using diffusion transformers for media generation may require evaluating attention over extremely long sequences, with attention layers accounting f

First-Order Trajectory Matching: Fast Ensemble Predictions of Chaotic, Turbulent, Stochastic Systems

arXiv:2606.11138v1 Announce Type: new Abstract: We introduce First-Order Trajectory Matching (FTM), a surrogate-modeling method that learns the first-order local transport of probability mass from tra

Flexible Flows for Biological Sequence Design

arXiv:2606.10543v1 Announce Type: cross Abstract: Designing functional biological sequences requires navigating vast discrete spaces under strict evolutionary and biophysical constraints. Discrete Flo

FlexPath: Learned Semantic Path Priors for Image-Based Planning

arXiv:2606.10167v1 Announce Type: new Abstract: Recent learning-based path planners use neural networks to process visual map representations and approximate heuristics for classical search algorithms

FOGO: Forgetting-aware Orthogonalization Optimizer

arXiv:2606.10406v1 Announce Type: cross Abstract: We argue that forgetting is not confined to continual learning but is a general optimization phenomenon: during standard training, dominant mini-batch

From Context-Aware to Conflict-Aware: Generalizing Contrastive Decoding for Knowledge Conflict in LLMs

arXiv:2606.10298v1 Announce Type: new Abstract: When large language models generate from retrieved or augmented contexts, conflicts between external context and parametric priors remain a central reli

From Data Heterogeneity to Convergence: A Data-Centric Review of Federated Learning

arXiv:2606.10595v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising solution for data hunger in centralized learning. This paradigm enables privacy with multiple clien

From Genes to Tokens: a GWAS-inspired Approach for Interpretable Stylometric Analysis

arXiv:2606.09543v2 Announce Type: replace Abstract: This short paper introduces a stylometric interpretation method inspired by genome-wide association studies (GWAS). Each 'gene' token's association

researcharxiv-cs-cl

From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot

arXiv:2606.10861v1 Announce Type: cross Abstract: LLM-powered chatbots are increasingly embedded in everyday workflows, raising sustainability concerns due to their energy use. Most mitigation strateg

FSS-Net: Frequency-Spatial Synergy Network with Wavelet Attention for Carotid Artery Ultrasound Segmentation

arXiv:2606.10378v1 Announce Type: new Abstract: Accurate segmentation of carotid arteries in ultrasound imaging is critical for stroke risk assessment. However, speckle noise, low contrast, and blurre

Fusing Satellite Imagery and Planimetric Maps for Cross-View Localization

arXiv:2606.10166v1 Announce Type: new Abstract: Current cross-view localization methods predominantly rely on satellite imagery as the aerial modality. Although recent work explores planimetric maps (

GAGI: A Gini-Adjusted GDP-per-Capita Index for Distribution-Aware Macroeconomic Welfare Monitoring

arXiv:2606.09944v1 Announce Type: cross Abstract: GDP per capita is the default lens through which governibng bodies track the economic prosperity and consequences of economic events , yet it is blind

GaussTrace: Provenance Analysis of 3D Gaussian Splatting Models with Evidence-based LLM Reasoning

arXiv:2606.10612v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) is a powerful technique for creating high-fidelity 3D assets. However, the widespread sharing and iterative modification of

Generalized Conformal Predictive Systems Under Distributional Shifts

arXiv:2606.11044v1 Announce Type: cross Abstract: Conformal predictive systems (CPS) output calibrated bands of CDFs under exchangeability. We extend generalized CPS to non-exchangeable settings by en

Generation of Diverse and Functional Robot Designs using Superquadrics Parametrisation and Quality-Diversity

arXiv:2606.11037v1 Announce Type: new Abstract: Generative design of robots requires navigating a vast search-space, encompassing physical configurations and behavioural parameters. Evolutionary Algor

Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions

arXiv:2606.10942v1 Announce Type: cross Abstract: As artificial intelligence and machine learning (AI/ML) models become integral to network operations, their lack of transparency poses a significant b

Geometric Formulation of Unified Force-Impedance Control on SE(3) for Robotic Manipulators

arXiv:2504.17080v3 Announce Type: replace Abstract: In this paper, we present an impedance control framework on the SE(3) manifold, which enables force tracking while guaranteeing passivity. Building

Geometrically Averaged Hard Target Updates for Linear Q-Learning

arXiv:2606.10835v1 Announce Type: cross Abstract: Periodic hard target updates are among the most common stabilization devices in modern deep Q-learning. Recent studies suggest that target updates can

Geometry-Aware Anisotropic Boundary Correction for Aerodynamic Simulation

arXiv:2606.09963v1 Announce Type: cross Abstract: Aerodynamic simulation is a key component of engineering shape design, where core quantities such as the surface pressure coefficient strongly depend

Glove2Hand: Synthesizing Natural Hand-Object Interaction from Multi-Modal Sensing Gloves

arXiv:2603.20850v2 Announce Type: replace Abstract: Understanding hand-object interaction (HOI) is fundamental to computer vision, robotics, and AR/VR. However, conventional hand videos often lack ess

Gradient based Bilevel for Inverse Optimal Control, a Riemannian approach

arXiv:2606.10841v1 Announce Type: new Abstract: Inverse Optimal Control (IOC) aims to recover the cost function that explains observed trajectories as solutions of an optimal control problem. Classica

GRAFT: Gain-Recalibrated Adapters for Transformer-Based Neural Population Activity Modeling

arXiv:2606.11066v1 Announce Type: new Abstract: Neural population activity models can recover rich temporal structure from binned spikes, but their read-in and readout layers often remain tied to a fi

GRAR: Glass-induced Reflection Artifact Removal in LiDAR Point Clouds

arXiv:2606.10541v1 Announce Type: new Abstract: Terrestrial Laser Scanning (TLS) point clouds captured in urban environments frequently suffer from glass-induced reflection artifacts, severely degradi

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators

arXiv:2602.22352v2 Announce Type: replace-cross Abstract: With the continuous growth of neural network scales, low-precision quantization is widely used in edge accelerators. Classic multi-threshold a

Hasse Diagrams for Attention: A Partial Order Framework for Designing Transformer Masks

arXiv:2606.09951v1 Announce Type: new Abstract: During the training of large Transformer models, attention masks regulate the scope and direction of information flow across a sequence. Numerous mask v

HMAF: A Hierarchical Multi-Slot GD-RTB Allocation Framework

arXiv:2606.09896v1 Announce Type: cross Abstract: In modern online advertising platforms, Guaranteed Delivery (GD) contracts coexist and bid with Real-Time Bidding (RTB) auctions. Recent approaches ei

How Does Reasoning Flow? Tracing Attention-Induced Information Flow for Targeted RL in LLMs

arXiv:2606.10646v1 Announce Type: cross Abstract: Token-level credit assignment remains a key obstacle for reinforcement learning (RL) in large language models (LLMs), where RL recipes typically treat

researcharxiv-cs-cl

Human-AI Teaming Through the Lens of Calibration

arXiv:2606.10906v1 Announce Type: cross Abstract: We study models for human-AI teaming through the lens of statistical calibration. We assume the team consists of an AI model and human -- both of whic

Hyperbolic Neural Population Geometry Benefits Computation

arXiv:2606.10238v1 Announce Type: cross Abstract: Neural population geometry shapes downstream computation. Recent empirical findings in neurobiology suggest that a hyperbolic structure underlies popu

iMessage is one of the most used messaging channels in America. Yet support for it in personal assistants has always been fragile. We partne…

iMessage is one of the most used messaging channels in America. Yet support for it in personal assistants has always been fragile. We partnered with @NousResearch to fix that. Now anyone can connect t

researchnous-research--x

Importance-Aware Scheduling for High-Dimensional Hyperparameter Optimization

arXiv:2606.10068v1 Announce Type: cross Abstract: Hyperparameter Optimization (HPO) is essential for building high-performing ML/DL models, yet conventional optimizers often struggle in high-dimension

Improved Representation of Matrix Lie Group Operations through Tensor Notation

arXiv:2606.10289v1 Announce Type: new Abstract: Several recent papers have demonstrated the utility of using Lie groups within estimation problems, yielding improved accuracy and consistency. This pap

In Defense of Cosine Similarity: Normalization Eliminates the Gauge Freedom

arXiv:2602.19393v2 Announce Type: replace Abstract: Steck, Ekanadham, and Kallus [arXiv:2403.05440] demonstrate that cosine similarity of learned embeddings from matrix factorization models can be ren

Inside the Latent Flow: Causal Deciphering of Attention Dynamics in Audio Separation Foundation Models

arXiv:2606.10046v1 Announce Type: cross Abstract: Flow-matching transformers achieve strong audio separation, yet their attention dynamics are opaque. We adapt established causal-intervention principl

Integral Field Unit Spectroscopy with One Fiber

arXiv:2606.10197v1 Announce Type: cross Abstract: Integral field unit (IFU) spectroscopy provides spatially resolved spectra across galaxies, offering crucial insights into their evolution. However, i

Integrating Biological-Informed Recurrent Neural Networks for Glucose-Insulin Dynamics Modeling

arXiv:2503.19158v3 Announce Type: replace Abstract: Type 1 Diabetes (T1D) management is a complex task due to many variability factors. Artificial Pancreas (AP) systems have alleviated patient burden

Integrating Out, Twice:The Open-System Case That Neural-Network Ensemble Theory Is Missing

arXiv:2606.09950v1 Announce Type: new Abstract: Averaging a neural network over its random parameters and marginalizing a Gaussian sector are the same operation, the Schur complement of the eliminated

Interactions Between Crosscoder Features: A Compact Proofs Perspective

arXiv:2606.09940v1 Announce Type: cross Abstract: Dictionary learning methods like Sparse Autoencoders (SAEs) and crosscoders attempt to explain a model by decomposing its activations into independent

Interpreting and Steering a Text-to-Speech Language Model with Sparse Autoencoders

arXiv:2606.10029v1 Announce Type: cross Abstract: Language models increasingly serve as the backbone of text-to-speech (TTS) systems, yet we understand little about the representations they build when

inversedMixup: Data Augmentation via Inverting Mixed Embeddings

arXiv:2601.21543v3 Announce Type: replace Abstract: Mixup generates augmented samples by linearly interpolating inputs and labels with a controllable ratio. However, since it operates at the latent em

researcharxiv-cs-cl

Is Task-Specific Training Necessary for Anomaly Detection?

arXiv:2601.22763v3 Announce Type: replace Abstract: Current state-of-the-art multi-class unsupervised anomaly detection (MUAD) methods rely on training encoder--decoder models to reconstruct anomaly-f

JOIN: Anchor-Grasp-Conditioned Joining via Opposition, Inference, and Navigation for Bimanual Assistive Manipulation

arXiv:2606.11151v1 Announce Type: new Abstract: Assistive mobility and manipulation platforms have received increasing attention as a means of restoring independence to individuals with disabilities.