Search: “framework”

High-Fidelity One-Step Generative Visuomotor Policy via Recursive Correction, Frequency Consistency, and Contrastive Flow Matching

arXiv:2607.03865v1 Announce Type: cross Abstract: Generative models such as diffusion and flow matching have advanced robotic visuomotor policies by modeling multimodal action distributions, but their

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Research

HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control

DGX agent

arXiv:2607.03449v1 Announce Type: cross Abstract: Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and r

researcharxiv-cs-ai

7 Jul 2026

HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders

arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i

applicationsarxiv-cs-cl

Agents

Homer: Understanding Long-form Videos with Hierarchical Memory and Agentic Reasoning

arXiv:2607.02588v1 Announce Type: cross Abstract: Multimodal large language models excel on short clips but struggle on hour-long videos in an online setting, where frames are processed incrementally

agentsarxiv-cs-ai

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation

arXiv:2607.03831v1 Announce Type: cross Abstract: Diffusion models have recently been repurposed for zero-shot classification, giving rise to diffusion classifiers that identify the best-matching text

HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors

arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt

applicationsarxiv-cs-ro

Human-Centric Reflective Architecture for Human-AI Collaborative Decision-Making

arXiv:2607.03025v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) across diverse areas of human activity-ranging from everyday tasks to safety-critical applications-aims to enhan

HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis

arXiv:2603.01121v2 Announce Type: replace Abstract: While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable c

Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles

arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit

applicationsarxiv-cs-cv

Hyper-KGGen: A Skill-Driven Knowledge Extractor for High-Quality Knowledge Hypergraph Generation

model-releasesarxiv-cs-cl

arXiv:2602.19543v2 Announce Type: replace Abstract: Knowledge hypergraphs surpass traditional binary knowledge graphs by encapsulating complex n-ary atomic facts, providing a more comprehensive paradi

Hardware

HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion

arXiv:2607.03012v1 Announce Type: cross Abstract: Video Diffusion Transformers (VDiTs) have demonstrated significant capabilities in high-fidelity video generation. However, their ability to produce l

hardwarearxiv-cs-ai

IBIS: A Hybrid Inception-BiLSTM and SVM Ensemble for Robust Doppler-based Human Activity Recognition

arXiv:2510.24936v3 Announce Type: replace Abstract: Wi-Fi sensing is a leading technology for Human Activity Recognition (HAR), offering a non-intrusive and cost-effective solution for healthcare and

applicationsarxiv-cs-cv

iFLYTEK-Embodied-Omni Technical Report

arXiv:2607.02542v1 Announce Type: new Abstract: General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actio

InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection

arXiv:2607.03795v1 Announce Type: new Abstract: Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based meth

InSpace: Structure-Aware 3D Indoor Scene Generation from a Single 360{eg} Image

arXiv:2607.03990v1 Announce Type: new Abstract: Recent advances in single image-to-3D generation have enabled high-quality asset synthesis, yet extending these capabilities to indoor scene generation

researcharxiv-cs-cv

Integrated Graph Search and Model Predictive Control for Smooth and Efficient Path Planning in Autonomous Vehicles

arXiv:2607.04259v1 Announce Type: new Abstract: Path planning is a fundamental component of autonomous vehicles, where achieving safe, comfortable, and dynamically feasible paths while ensuring comput

safetyarxiv-cs-ro

Integrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal Data

model-releasesarxiv-cs-lg

arXiv:2607.04647v1 Announce Type: cross Abstract: Scalable Bayesian inference for generalized linear mixed models (GLMMs) provides uncertainty-aware analysis of correlated longitudinal data, but exist

Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

arXiv:2607.05393v1 Announce Type: cross Abstract: Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable la

Local Ai

Interpretable Nanoporous Materials Design with Symmetry-Aware Networks

arXiv:2509.15908v3 Announce Type: replace-cross Abstract: Nanoporous materials hold promise for diverse sustainable applications, yet their vast chemical space poses challenges for efficient design. M

local-aiarxiv-cs-ai

InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem

arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina

IRIS: An Intelligent Vision-Language System for Ocular Surface Diseases via Topic Tree and Scene-Driven VQA Generation

arXiv:2607.04344v1 Announce Type: cross Abstract: While Large Vision-Language Models (VLMs) demonstrate remarkable generic capabilities, their clinical reasoning in specialized domains like ocular sur

JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference

arXiv:2512.22999v2 Announce Type: replace-cross Abstract: We consider problems of parameter estimation where design variables can be actively optimized to maximize information gain. To this end, we in

Jointly Improving Dialect Identification and ASR in Indian Languages using Multimodal Feature Fusion

arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit signifi

researcharxiv-cs-cl

Local Ai

KAM-WM: Kinematic Affordance Maps from Latent World Models for Robot Manipulation

arXiv:2607.04652v1 Announce Type: new Abstract: Learning manipulation from few demonstrations requires visual priors that capture not only where to interact, but also how the interaction should begin;

local-aiarxiv-cs-ro

KinEMbed: Decoding Kinematics from Electromyography via Cross-Modal Contrastive Learning

arXiv:2607.04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic

LACE-SVD: Loss-Aware SVD with Cumulative Error Correction for LLM Compression

arXiv:2607.03057v1 Announce Type: cross Abstract: The rapid growth in the parameter scale of large language models (LLMs) has created a strong demand for efficient compression techniques. As a hardwar

Lacuna Inc. at SemEval-2026 Task 4: Structurally Gated State-Space Models for Disentangling Narrative Similarity

arXiv:2607.03482v1 Announce Type: new Abstract: In this paper, we present the Invariant-Variant Disentangled State-Space Model (IVD-SSM), our submission to SemEval-2026 Task 4 on Narrative Story Simil

safetyarxiv-cs-cl

Language Generation with Replay: A Learning-Theoretic View of Model Collapse

arXiv:2603.11784v2 Announce Type: replace Abstract: As scaling laws push the training of frontier large language models (LLMs) toward ever-growing data requirements, training pipelines are approaching

Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments

arXiv:2412.13533v4 Announce Type: replace Abstract: Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown prom

Language Models Represent and Transform Concepts with Shared Geometry

arXiv:2607.04525v1 Announce Type: cross Abstract: How concepts are represented in neural networks is a fundamental question in machine learning. The dominant view treats concept representations as sta

Last-Meter Precision Navigation for UAVs: A Diffusion-Refined Aerial Visual Servoing Approach

arXiv:2607.04352v1 Announce Type: new Abstract: In this work, we study the last-meter precision navigation for UAVs, e.g., autonomously reaching a target within the final 10 meters using monocular vis

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers

arXiv:2607.04819v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables computation on encrypted data, but practical encrypted Transformer inference is bottlenecked by the sequentia

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation

arXiv:2607.04270v1 Announce Type: cross Abstract: Large language models (LLMs) have recently emerged as powerful backbones for recommender systems by reformulating recommendation as a token-level gene

LBTCap: A Lightweight Bilateral Transformer for Real-Time Remote Sensing Image Change Captioning

arXiv:2607.03320v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) generates natural-language descriptions of semantic changes between paired remote sensing images (RSIs),

researcharxiv-cs-cv

Learning from Lost Provenance: Multiple Instance Learning for Cancer Registry Tumor Group Classification

arXiv:2607.03481v1 Announce Type: new Abstract: Modernizing cancer registries with deep learning is opening new opportunities to automate labor-intensive tasks such as the coding of pathology reports.

researcharxiv-cs-cl

Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses

arXiv:2406.14340v2 Announce Type: replace-cross Abstract: The standard stochastic gradient descent (SGD) optimization method, as well as adaptive methods such as the Adam optimizer fail to converge if

Learning Structured Visual Compositional Representations for Weakly Supervised Referring Expression Comprehension

arXiv:2607.04638v1 Announce Type: new Abstract: Referring expression comprehension (REC) aims to localize the object in an image described by natural language. In Weakly supervised REC (WREC), existin

safetyarxiv-cs-cv

Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal Models

arXiv:2607.02909v1 Announce Type: cross Abstract: Taxonomies provide key information about the semantic relationships between concepts and the inherent organization of vision and language. Despite the

Learning with the Nash-Sutcliffe loss

arXiv:2603.00968v2 Announce Type: replace-cross Abstract: The Nash-Sutcliffe efficiency (ext{NSE}) is a widely used, positively oriented relative measure for evaluating forecasts across multiple time

LILAC: Layer-Wise Independent LoRAs and Cascaded Conditioning for Multi-Concept Customization of Diffusion Models

arXiv:2607.04801v1 Announce Type: new Abstract: Personalizing text-to-image diffusion models to render several specific subjects in a coherent image remains challenging: the model must preserve each s

LLM-as-a-Tutor: Policy-Aware Prompt Adaptation for Non-Verifiable RL

arXiv:2607.04412v1 Announce Type: new Abstract: Reinforcement learning (RL) for non-verifiable instruction following increasingly relies on LLM judges with prompt-specific rubrics as reward signals. W

Local Constrained Bayesian Optimization

arXiv:2603.07965v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) for high-dimensional constrained problems remains a significant challenge due to the curse of dimensionality. We pr

Localized LoRA-MoE: Block-wise Low-Rank Experts With Adaptive Routing

arXiv:2607.05114v1 Announce Type: cross Abstract: Large Language Models (LLMs) and high-dimensional perception networks increasingly rely on parameter-efficient fine-tuning (PEFT) to adapt to diverse

Look Before You Leap: Distilling Tree Search into Action Evaluation for Frozen VLA Models

arXiv:2607.03751v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models acquire broad embodied capabilities through large-scale pretraining, yet their generalization remains far more fragi

researcharxiv-cs-ro

LRX-PINN: A Layer-Resolving XNet Physics-Informed Neural Network with Integrated Cauchy Activations for Convection-Dominated Problems

arXiv:2607.03682v1 Announce Type: cross Abstract: Convection-dominated convection-diffusion problems often develop thin layers, where the solution has sharp transition profiles and its derivatives are

Lyapunov-Guided Training for Hardware-Safe Neural Networks Under Fixed-Point Arithmetic

arXiv:2607.04531v1 Announce Type: cross Abstract: Low-precision neural networks are attractive for resource-constrained hardware, but fixed-point arithmetic introduces failure modes that are often hid

Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk

arXiv:2510.25147v3 Announce Type: replace Abstract: To mitigate acute wildfire ignition risks, utilities de-energize power lines in high-risk areas. The Optimal Power Shutoff (OPS) problem optimizes l

MACS: Measurement-Aware Consistency Sampling for Inverse Problems

arXiv:2510.02208v3 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative priors for solving inverse imaging problems. However, their practical deployment is hinde

researcharxiv-cs-cv