Search: “framework”

arXiv:2606.09355v1 Announce Type: new Abstract: Robust inertial odometry is essential for various carriers when external sensing is unreliable. Learning-based methods reduce integration drift by captu

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Research

MotionGPT-2: A General-Purpose Motion-Language Model for Motion Generation and Understanding

DGX agent

arXiv:2410.21747v2 Announce Type: replace Abstract: Generating lifelike human motions from descriptive texts has experienced remarkable research focus in the recent years, propelled by the emerging re

researcharxiv-cs-cv

9 Jun 2026

MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation

arXiv:2606.09215v1 Announce Type: new Abstract: World Action Models (WAMs) couple a video dynamics prior to the policy and have shown encouraging results on tabletop manipulation, but iterative denois

safetyarxiv-cs-ro

Multi-resolution Enhancement for Full Spectrum Neural Representations

arXiv:2509.15494v2 Announce Type: replace Abstract: Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-based representations increasingly intractable. Imp

Applications

Multi-View Speech Representation Learning for Parkinson's Disease Detection Using Context-guided Cross-modal Attention

arXiv:2606.09271v1 Announce Type: cross Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria.

applicationsarxiv-cs-lg

Multimodal Large Language Models as Synthetic Participants in Video-Based Studies: An Evaluation

arXiv:2606.07541v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong performance on objective tasks such as video understanding and reasoning. However, it remai

Tutorials

Neural Legendre-Fenchel transform with Hessian Preconditioning

arXiv:2606.09077v1 Announce Type: new Abstract: The Legendre-Fenchel (LF) transform is a fundamental tool in convex analysis and machine learning that maps lower semi-continuous functions to their con

tutorialsarxiv-cs-lg

NeuroAlign: Hierarchical Multimodal Fusion of Dynamic and Structural Neuroimaging for MCI Analysis

arXiv:2606.07635v1 Announce Type: cross Abstract: Multimodal neuroimaging fusion of functional MRI (fMRI) and diffusion tensor imaging (DTI) provides complementary information for cognitive impairment

New Fractional Ambiguity Function Integrated with CNN-Based Machine Learning for Signal Classification

arXiv:2606.08110v1 Announce Type: cross Abstract: A new fractional ambiguity function (NFrAF) derived from the fractional Fourier transform is introduced as a generalization of the classical ambiguity

No Free Lunch for Synthetic Images under Data Scarcity Conditions

arXiv:2606.07640v1 Announce Type: cross Abstract: This study investigates the trade-offs between fidelity, privacy, and utility in synthetic data generation under conditions of data scarcity and priva

researcharxiv-cs-ai

No Modality Left Behind: Adapting to Missing Modalities via Knowledge Distillation for Brain Tumor Segmentation

arXiv:2509.15017v2 Announce Type: replace Abstract: Accurate brain tumor segmentation is essential for preoperative evaluation and personalized treatment. Multi-modal MRI is widely used due to its abi

safetyarxiv-cs-cv

Normality Calibration in Semi-supervised Graph Anomaly Detection

arXiv:2510.02014v3 Announce Type: replace Abstract: Graph anomaly detection (GAD) has attracted growing interest for its crucial ability to uncover irregular patterns in broad applications. Semi-super

NutriMLLM: Multimodal Large Language Models for Dietary Micronutrient Analysis

arXiv:2606.08948v1 Announce Type: cross Abstract: Comprehensive estimation of dietary micronutrients from food images could improve clinical nutrition care, but training such models requires large mul

OASIS: From Simulation Data Collection to Real-World Humanoid Loco-Manipulation

arXiv:2606.08548v1 Announce Type: new Abstract: Recent progress in robot manipulation has been largely driven by learning from large-scale demonstrations. For humanoid robot loco-manipulation tasks, h

safetyarxiv-cs-ro

Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark

arXiv:2606.07550v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) offers a promising route for developing plasma controllers from historical tokamak data, since online trial-and-er

omega-EVA: Envision, Verify, and Act with Latent Interactive World Models

arXiv:2606.09457v1 Announce Type: new Abstract: Embodied policies typically map current observations directly to actions, leaving candidate-action consequences implicit. World models provide predictiv

safetyarxiv-cs-ro

OmniCap-IF: Benchmarking and Improving Instruction Following Abilities for Omni-Video Captioning

arXiv:2606.08572v1 Announce Type: new Abstract: While Omni-modal Large Language Models (OLLMs) have demonstrated impressive capabilities in jointly processing audio and visual streams, their ability t

OmniGen-AR: AutoRegressive Any-to-Image Generation

arXiv:2606.09156v1 Announce Type: new Abstract: Autoregressive (AR) models have demonstrated strong potential in visual generation, offering superior performance with simple architectures and optimiza

OmniMem: Perturbation-aware Memory Compression for Streaming Audio-Visual LLMs

arXiv:2606.07577v1 Announce Type: new Abstract: Audio-visual large language models (LLMs) hold strong promise for long-form video understanding, yet their long-video inference is fundamentally limited

OmniTryOn: Video Try-On Anything at Once!

arXiv:2606.08514v1 Announce Type: new Abstract: Although video virtual try-on (VVT) has achieved significant progress, existing methods still exhibit two fundamental limitations: first, they are restr

One Stone, Three Birds: Self-adaptive Optimal Transport for Multi-VLM Selection, Adaptation, and Ensembling

arXiv:2606.08126v1 Announce Type: new Abstract: Vision-language models (VLMs) enable visual recognition from semantic class descriptions, which makes them attractive when target annotations are scarce

researcharxiv-cs-cv

Agents

Online Agent-as-a-Judge: Situation-Generating Evaluation for Interactive Agents

arXiv:2606.08200v1 Announce Type: new Abstract: Evaluating LLM-powered interactive social agents is challenging because socially relevant behaviors depend not only on isolated outputs, but also on pri

agentsarxiv-cs-ai

Operationalising the Superficial Alignment Hypothesis via Task Complexity

arXiv:2602.15829v2 Announce Type: replace Abstract: The superficial alignment hypothesis (SAH) posits that large language models learn most of their knowledge during pre-training, and that post-traini

Operator learning for solving Fokker-Planck equations with various initial conditions

arXiv:2606.09434v1 Announce Type: new Abstract: The Fokker-Planck equation (FPE) plays a pivotal role in describing the time evolution of probability density functions (PDFs) for systems governed by s

Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints

arXiv:2601.23221v2 Announce Type: replace Abstract: As acquiring reliable ground-truth labels is usually costly, or infeasible, crowdsourcing and aggregation of noisy human annotations is the typical

Optimizing Energy-based Neural Network Training with Coherent Ising Machine

arXiv:2606.09117v1 Announce Type: cross Abstract: While Ising machines serve as advanced physical solvers for the Ising model,enabling applications in combinatorial optimization and neural network tra

researcharxiv-cs-ai

Optimizing Few-Step Generation with Adaptive Matching Distillation

arXiv:2602.07345v2 Announce Type: replace Abstract: Distribution Matching Distillation (DMD) is a powerful acceleration paradigm, yet its stability is often compromised in Forbidden Zone, regions wher

researcharxiv-cs-cv

Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution

arXiv:2606.08904v1 Announce Type: new Abstract: Macro placement is a fundamental step in modern chip physical design, playing a crucial role in determining the solution quality of high-dimensional com

researcharxiv-cs-ai

Outage Detection in Self-Healing Smart Grids Using Reinforcement Learning with Spectral Graph Neural Networks

arXiv:2606.07583v1 Announce Type: cross Abstract: Self-healing smart grids can quickly adjust their network configuration during outages to minimize power disruptions. During an outage, several action

Overcoming the Limits of Finite Difference Method; Physics-Informed Neural Network for Noisy High-Dimensional Heat Diffusion

arXiv:2606.07982v1 Announce Type: new Abstract: High-dimensional transient heat diffusion under noisy boundary conditions exposes a fundamental limitation of classical numerical methods: accuracy degr

pacSTL: PAC-Bounded Signal Temporal Logic from Data-Driven Reachability Analysis

arXiv:2511.00934v2 Announce Type: replace-cross Abstract: Signal Temporal Logic (STL) is an expressive language for specifying behaviors of dynamical systems from continuous signals. However, a limita

researcharxiv-cs-ro

PACT: Learning Diverse Diagnostic Strategies via Privileged Synthesis and Branch Consensus

arXiv:2606.08938v1 Announce Type: cross Abstract: Clinical diagnosis requires flexible use of multiple reasoning paradigms under incomplete patient information. Existing LLM-based medical agents show

PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation

arXiv:2606.08414v1 Announce Type: cross Abstract: Diffusion policies have achieved remarkable success in robotic manipulation, yet they often fail to satisfy strict physical constraints required for s

PAEC: Position-Aware Entropy Calibration for LLM Reasoning in RLVR

arXiv:2606.08543v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves large language model reasoning but often suffers from rapid policy-entropy collapse, wher

PAFO: Pareto Fairness Optimization for Personalized Reward Modeling

arXiv:2606.07988v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on reward models to align their outputs with diverse user preferences. While personalized reward models a

Pantheon360: Taming Digital Twin Generation via 3D-Aware 360{eg} Video Diffusion

arXiv:2605.25449v2 Announce Type: replace Abstract: Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constr

researcharxiv-cs-cv

PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow

arXiv:2606.07549v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patc

Local Ai

Perceptive Behavior Foundation Model: Adapting Human Motion Priors to Robot-Centric Terrain

arXiv:2606.08059v1 Announce Type: new Abstract: Humanoid behavior foundation models aim to acquire reusable whole-body control policies from broad human motion priors, enabling a single controller to

local-aiarxiv-cs-ro

PereStruct: Multimodal Semantic Assembly for Robust Historical Document Parsing

arXiv:2606.07661v1 Announce Type: new Abstract: Parsing historical documents with complex, non-standard layouts remains a fundamental bottleneck in large-scale archival digitization. Unlike modern typ

Agents

Perturbative Contrastive Physical Learning

arXiv:2606.09756v1 Announce Type: new Abstract: Responses to perturbations are key to understanding physical systems. The ability to contrast such responses by comparing how a system reacts under slig

agentsarxiv-cs-lg

Phantom transitions in language model fine-tuning

arXiv:2606.07559v1 Announce Type: cross Abstract: Fine-tuning a language model on contexts whose correct completion has a near-synonym competitor often fails silently. The cross-entropy loss decreases

Pharmacogenomic Knowledge Graph Augmentation for Graph Neural Network-Based Drug-Drug Interaction Prediction

arXiv:2606.07698v1 Announce Type: cross Abstract: Graph neural networks (GNNs) applied to drug-drug interaction (DDI) prediction rely exclusively on molecular structure encoded as SMILES-derived graph

Local Ai

PhysAgent: Automating Physics-Based 4D Synthesis via Trajectory-Grounded Multi-Agent Feedback

arXiv:2606.08688v1 Announce Type: cross Abstract: Achieving fully automated, physically plausible 3D motion synthesis is a core objective in graphics and generative AI. However, configuring complex en

local-aiarxiv-cs-cv

Applications

PhysGraph: A Physics-aware 3D Scene Graph for Perception and Reasoning

arXiv:2606.08655v1 Announce Type: cross Abstract: To perform a wide range of daily tasks, robots need to construct a 3D representation that is semantically rich, physically grounded, and structured en

applicationsarxiv-cs-cv

Physically Consistent Null Space Alignment for Detection of Low-Magnitude False Data Injection Attacks

arXiv:2606.08473v1 Announce Type: new Abstract: False data injection attacks (FDIAs) introducing small measurement perturbations can still cause large deviations in power system state estimation when

Applications

Physics-Aware Sparse Learning and Selective Online Adaptation for Euler-Lagrange Robot Dynamics

arXiv:2606.09640v1 Announce Type: new Abstract: Accurate dynamics models are essential for model-based robotic control, yet nominal Euler--Lagrange models often become inaccurate in the presence of pa

applicationsarxiv-cs-ro

Physics-Guided Dual Decoding and Spectral Supervision for Global 3D Hydrometeor Prediction

arXiv:2606.08563v1 Announce Type: new Abstract: While global data-driven models excel at predicting continuous atmospheric variables, three-dimensional hydrometeor forecasting remains challenging due

POET-X: Memory-efficient LLM Training by Scaling Orthogonal Transformation

arXiv:2603.05500v2 Announce Type: replace-cross Abstract: Efficient and stable training of large language models (LLMs) remains a core challenge in modern machine learning systems. To address this cha