All entries

Fine-grained Human Motion Understanding with Language Models

arXiv:2606.20888v1 Announce Type: new Abstract: In this work, we propose methodname, an LLM-based model for fine-grained human motion understanding that represents motion as a sequence of skeletal pos

researcharxiv-cs-cv

Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study

DGX agent

arXiv:2602.17431v2 Announce Type: replace-cross Abstract: Uncertainty quantification has emerged as an effective approach to closed-book hallucination detection for LLMs, but existing methods are larg

researcharxiv-cs-lg

23 Jun 2026

Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think

model-releasesarxiv-cs-ro

arXiv:2606.20246v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models pre-trained on massive video-robot datasets have revolutionized robotic manipulation, yet their multi-billion pa

Finite-Sample Performance of Gradient Descent in Logistic Regression with Gaussian Design

arXiv:2606.21683v1 Announce Type: cross Abstract: We consider the parameter estimation problem in logistic regression with Gaussian design: the estimation of a fixed unknown parameter heta^*in R^d (|h

Industry

First Southwest Airlines flight with Starlink!

Southwest Airlines operated its first flight equipped with Starlink satellite internet connectivity, marking a milestone in the adoption of Elon Musk's satellite internet service for commercial aviati

industryelon-musk--x

FirstPass: Grounding AI Scientific Judgment in Multi-Round Editorial Outcomes

arXiv:2606.20769v1 Announce Type: cross Abstract: AI systems for peer review fail on three fronts: they train on Computer Science and Machine Learning venues alone, ignore the iterative dialogue that

Agents

Five thoughts from Swami Sivasubramanian’s keynote at AWS Summit and what it means for IT pros

When Amazon Web Services Inc. held its New York Summit last week, Vice President of Agentic AI Swami Sivasubramanian as usual was the headline act, delivering the opening keynote. Sivasubramanian made

agentssiliconangle

Flatness Preserves Instruction Following in Vision-Language-Action Models

arXiv:2606.23641v1 Announce Type: new Abstract: Vision-language-action (VLA) models have the potential for open-world generalization by leveraging pretrained vision-language representations, yet downs

Hardware

FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages

arXiv:2606.21222v1 Announce Type: new Abstract: Large-scale autonomous fleets rely on teleoperation to resolve rare failures, yet streaming raw sensor data from many vehicles is costly, and remote ope

hardwarearxiv-cs-ro

FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation

arXiv:2606.23370v1 Announce Type: cross Abstract: Device-side Large Language Models (LLMs) have grown explosively, offering stronger privacy and higher availability than their cloud-side counterparts.

FLFL: Federated Latent Factor Learning for Private Recovery of Spatio-Temporal Signals

arXiv:2606.23091v1 Announce Type: new Abstract: Wireless sensor network (WSNs) stands out as a burgeoning and promising domain in intelligent sensing. Owing to various factors such as sudden sensor ma

applicationsarxiv-cs-lg

Industry

Flipkart says it plans to expand its network of micro-fulfillment centers in India to 1,500 by the end of 2026, as it also claims orders have grown ~400% YoY (Jagmeet Singh/TechCrunch)

Jagmeet Singh / TechCrunch: Flipkart says it plans to expand its network of micro-fulfillment centers in India to 1,500 by the end of 2026, as it also claims orders have grown ~400% YoY — As quick com

industrytechmeme

Local Ai

FLM-Occ: Feed-forward Likelihood Maximization for Efficient Indoor Occupancy Prediction

arXiv:2606.21373v1 Announce Type: new Abstract: Recent indoor occupancy prediction methods adopt Gaussian primitives as a sparse 3D representation for computational efficiency. However, their training

local-aiarxiv-cs-cv

Flow Annealing Posterior Sampling for Function-Space Regression and Inverse Problems

arXiv:2606.22346v1 Announce Type: cross Abstract: Principled regression for stochastic processes is a long-standing challenge with deep connections to scientific inverse problems. We introduce Flow An

Flow as Flow: Modeling Robot Velocity Fields as Probability Velocity Fields for Flow-Based Object Manipulation

arXiv:2606.23090v1 Announce Type: new Abstract: Cross-embodiment data have become central to training robotic foundation models. To leverage such heterogeneous data, we focus on flow-based object mani

Flow Matching for Efficient and Scalable Data Assimilation

arXiv:2508.13313v5 Announce Type: replace-cross Abstract: Data assimilation (DA) estimates a dynamical system's state from noisy observations. Recent generative models like the ensemble score filter (

Local Ai

Flow6D: Discrete-to-Continuous Flow Matching for Efficient and Accurate Category-Level 6D Pose Estimation

arXiv:2606.23293v1 Announce Type: new Abstract: 6D pose estimation is a key task in computer vision and embodied AI, widely used in robotic manipulation, augmented reality, etc. Existing methods direc

local-aiarxiv-cs-cv

FlowCodec: One-Step Flow Prior for Generative Image Compression

arXiv:2606.21030v1 Announce Type: cross Abstract: Diffusion-based image compression methods, leveraging powerful generative priors, have demonstrated remarkable perceptual quality at ultra-low bitrate

FlowDec: Temporal Conditional Flow Decorruptor for Robust Continuous Vision-Language Navigation

arXiv:2606.22424v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to follow natural-language instructions in unseen scenes. While Large

applicationsarxiv-cs-cv

FlowDPG: Deterministic Policy Gradient on Flow Matching Policies for Real-World Manipulation

arXiv:2606.22303v1 Announce Type: new Abstract: Real-world reinforcement learning for robotic manipulation remains challenging, and this difficulty is amplified for flow matching policies: applying po

safetyarxiv-cs-ro

Flowing With Purpose: Latent Action Guided Flow Matching Policies For Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.23420v1 Announce Type: new Abstract: Flow matching has recently become a new standard for behavior cloning in robotic manipulation. However, state-of-the-art flow matching policies suffer f

FlowTrain: Flow-Based Decoupled Training for Industrial-Grade Vision-Language Models

arXiv:2606.23087v1 Announce Type: new Abstract: Industrial-grade distributed training of vision-language models (VLMs) remains far less efficient than that of unimodal LLMs. Existing solutions either

applicationsarxiv-cs-lg

FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation

arXiv:2606.20867v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models enable general-purpose robotic control via large-scale multimodal pretraining, yet their effectiveness under few-sho

Following the Flow: Advection-Consistent Modeling for Event-based Small Object Detection

arXiv:2606.22378v1 Announce Type: new Abstract: Event cameras enable high-frequency visual perception with microsecond latency, offering advantages for dynamic scenes. However, event-based small objec

FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs

arXiv:2606.19025v2 Announce Type: replace Abstract: Pre-training Large Language Models (LLMs) typically demands large-scale infrastructure with tightly coupled hardware accelerators. Mixture-of-Expert

Industry

For the last 46 years, it has been my privilege to work alongside countless talented artists and crews to create these characters, stories, …

For the last 46 years, it has been my privilege to work alongside countless talented artists and crews to create these characters, stories, and films for you all. I'm looking forward to seeing you at

industryelon-musk--x

ForeHOI: Feed-forward 3D Object Reconstruction from Daily Hand-Object Interaction Videos

arXiv:2602.06226v2 Announce Type: replace Abstract: The ubiquity of monocular videos capturing daily hand-object interactions presents a valuable resource for embodied intelligence. While 3D hand reco

researcharxiv-cs-cv

Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents

arXiv:2606.23085v1 Announce Type: new Abstract: Long-horizon tasks are common in real-world robotic deployments, yet failure detection for such tasks remains underexplored. Detecting failures in long-

FORGE: Fused On-Register Gradient Elimination for Memory-Efficient LLM Training

arXiv:2606.22932v1 Announce Type: new Abstract: Reverse-mode differentiation computes every weight gradient, writes it to memory, and only then lets the optimizer read it back. This two-phase schedule

Formalizing Task-Space Complexity for Zero-Shot Generalization

arXiv:2606.20967v1 Announce Type: new Abstract: Policies must operate across diverse conditions, yet a single policy is often conservative while fully adaptive schemes can be complex. We study zero-sh

safetyarxiv-cs-lg

Foundation Models for Epileptogenic Zone Identification in Drug-Resistant Epilepsy

arXiv:2606.22657v1 Announce Type: new Abstract: Accurate identification of the epileptogenic zone (EZ) is essential for seizure freedom after resective surgery in drug-resistant epilepsy, yet seizure

Tutorials

FPAS: Frontier-Based Path Planning with Adaptive Sampling for Large-Scale Unknown Environments

arXiv:2606.22838v1 Announce Type: new Abstract: In this work, we propose Frontier-based Path Planning with Adaptive Sampling (FPAS), a novel framework designed for efficient goal-reaching in large-sca

tutorialsarxiv-cs-ro

FPGA-Accelerated Neuromorphic Vision System for Real-Time Orbital Object Detection

arXiv:2606.20727v1 Announce Type: cross Abstract: The escalating congestion in orbital space demands advanced monitoring solutions. This work presents a comprehensive open-source framework for neuromo

Frequency-Domain Neural ODEs for Modeling Non-Linear Dynamical Systems

arXiv:2606.22075v1 Announce Type: new Abstract: Standard continuous-depth models, such as Neural Ordinary Differential Equations (NODEs), offer significant advantages in modeling physical systems by l

Frequency Response Identification of Low-Order Systems: Finite-Sample Analysis

arXiv:2508.17142v3 Announce Type: replace-cross Abstract: This paper proposes a frequency-domain estimator for low-order systems from repeated noisy measurements. The estimator minimizes a quadratic d

From Complaint Narratives to Monetary Relief: A Hybrid Machine Learning Framework for CFPB Consumer Complaints

arXiv:2606.22664v1 Announce Type: cross Abstract: Consumer financial complaints provide a valuable source of information for identifying service failures, dispute frictions, and operational deficienci

applicationsarxiv-cs-lg

From Convolution to Transformer: A Comparative Study of U-Net Variants for Brain Tumor and Retinal Vessel Segmentation

arXiv:2606.22168v1 Announce Type: new Abstract: Medical image segmentation plays an important role in computer aided diagnosis, treatment planning, and disease monitoring. U-Net has been widely used f

Agents

From Discrete Plans to Real-World Execution: A World-Model-Driven Framework for Execution-Aware Multi-Agent Path Finding

arXiv:2511.21886v2 Announce Type: replace Abstract: Multi-Agent Path Finding (MAPF) studies how to coordinate multiple agents to reach their goals without collisions and underpins a range of large-sca

agentsarxiv-cs-ro

From Driving Videos to Simulatable Scenarios

arXiv:2606.21993v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) face driving scenarios ranging from routine traffic to rare events. To assess safety it is crucial to reproduce these scenar

From Gradient Clipping to Structural Refinement: Improving DPSGD for Medical Image Segmentation

arXiv:2606.21763v1 Announce Type: new Abstract: Medical image segmentation is widely used for disease detection but relies on sensitive data, raising privacy concerns as trained models can leak inform

From Handcrafted Features to Functional Edge Learning: Evolution of EEG Seizure Detection Frameworks

arXiv:2606.22258v1 Announce Type: new Abstract: Electroencephalogram (EEG) analysis remains the clinical gold standard for epilepsy diagnosis and seizure detection. While Deep Learning (DL) has signif

From Knowing to Acting: Benchmarking Self-Awareness Capability of LLM Agents

arXiv:2606.20661v1 Announce Type: cross Abstract: The integration of external tools has transitioned LLM agents from passive responders to autonomous systems. However, current benchmarks prioritize ex

From Markov to Laplace: How Mamba In-Context Learns Markov Chains

arXiv:2502.10178v2 Announce Type: replace Abstract: While transformer-based language models have driven the AI revolution thus far, their computational complexity has spurred growing interest in viabl

From Pixels to Concepts: Growing Rich 3D Semantic Scene Graph Forests utilizing Foundation Models

arXiv:2606.23312v1 Announce Type: new Abstract: Operating in complex real-world environments requires robots to understand their surroundings on a functional semantic level. This demands a detailed mu

From Point Estimates to Distributions: GMM Pooling for MIL in Preterm Birth Prediction

arXiv:2606.23005v1 Announce Type: new Abstract: Preterm birth (PTB) prediction can enable targeted surveillance and timely intervention, yet most ultrasound-based models use a single selected transvag

From Reconstruction to Decision: A Post-Encoder Plug-in Adapter for Curvilinear Segmentation

arXiv:2606.23486v1 Announce Type: new Abstract: Curvilinear object segmentation, including vessels and cracks, is challenging due to extreme spatial sparsity and topological fragility, where small loc

From Speech to Text Corpora: Evaluating ASR-Based Data Acquisition for Low-Resource Fongbe and Hausa

arXiv:2606.22274v1 Announce Type: cross Abstract: Low-resource African languages lack text corpora needed for language model training. We investigate whether ASR pipelines can extend text resources fo

Tutorials

From Uncertainty to Stability and Fidelity: Guiding Sparse-View 3D Gaussian Splatting with Fisher Information

arXiv:2606.20842v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a promising technique for novel view synthesis. However, 3DGS requires dense input views to achieve high-qua

tutorialsarxiv-cs-cv