Search: “framework”

Generalizable and Actionable Parts Pose Estimation with Symmetry Annotation-Free Learning Strategy

arXiv:2605.17033v1 Announce Type: new Abstract: Urgently needed generalizable robot object interaction and manipulation requires high-quality Cross-Category object perception. As a pioneer of this are

researcharxiv-cs-ro

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Model Releases

Geometric Asymmetry in MoE Specialization: Functional Decorrelation and Representational Overlap

DGX agent

arXiv:2605.16349v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures achieve scalable capacity through sparse routing, yet the geometric structure of expert specialization remains po

model-releasesarxiv-cs-lg

19 May 2026

Geospatial-Reasoning-Driven Vocabulary-Agnostic Remote Sensing Semantic Segmentation

arXiv:2602.08206v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation has become an important direction in remote sensing, as it enables recognition beyond predefined land-cover ca

researcharxiv-cs-cv

GIM: Evaluating models via tasks that integrate multiple cognitive domains

arXiv:2605.18663v1 Announce Type: new Abstract: As LLM benchmarks saturate, the evaluation community has pursued two strategies to increase difficulty: escalating knowledge demands (GPQA, HLE) or remo

GLT-PEFT: Gated Lie-Tucker Parameter-Efficient Fine-Tuning for Alzheimer's Disease Diagnosis with Hippocampal Segmentation Pretraining

arXiv:2605.16769v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as a promising paradigm for adapting pretrained models under limited data conditions. However, most e

GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Games

arXiv:2508.08501v3 Announce Type: replace Abstract: We introduce GVGAI-LLM, a video game benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). Built

Haptic Rendering of Fractional-Order Viscoelasticity: Passivity and Rendering Fidelity

arXiv:2605.16389v1 Announce Type: cross Abstract: Haptic rendering of viscoelastic materials that exhibit creep and stress relaxation is crucial for many applications, such as medical training with re

researcharxiv-cs-ai

Helpful to a Fault: Measuring Illicit Assistance in Multi-Turn, Multilingual LLM Agents

arXiv:2602.16346v3 Announce Type: replace Abstract: LLM-based agents execute real-world workflows via tools and memory. These affordances enable ill-intended adversaries to also use these agents to ca

safetyarxiv-cs-cl

Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach

arXiv:2605.18437v1 Announce Type: new Abstract: Vehicular edge computing (VEC) enables latency-sensitive vehicular applications by offloading computation-intensive tasks to nearby edge servers. Howeve

safetyarxiv-cs-lg

Hilbert-Geo: Solving Solid Geometric Problems by Neural-Symbolic Reasoning

arXiv:2605.16385v1 Announce Type: cross Abstract: Geometric problem solving, as a typical multimodal reasoning problem, has attracted much attention and made great progress recently, however most of w

HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos

arXiv:2605.17543v1 Announce Type: new Abstract: Video outpainting generates plausible visual content beyond the original spatial extent of a video, playing a key role in adapting videos to diverse dis

researcharxiv-cs-cv

How Wrong Can Your Counterfactual Be? Quantifying Confounding Bias for Continuous Treatments without a Control Group

arXiv:2603.07438v2 Announce Type: replace Abstract: Stress testing poses a causal question: how would portfolio credit losses change if the macroeconomy followed an adverse counterfactual path? Yet st

HPC-LLM: Practical Domain Adaptation and Retrieval-Augmented Generation for HPC Support

model-releasesarxiv-cs-lg

arXiv:2605.16347v1 Announce Type: new Abstract: Modern scientific research increasingly depends on High-Performance Computing (HPC) infrastructures, yet many researchers face significant operational b

Identify Then Project: Contrastive Learning of Latent Dynamics from Partial Observations with Port-Hamiltonian Structure

arXiv:2605.16682v1 Announce Type: new Abstract: Identifying latent state representations and dynamics is essential when direct modeling in observation space is infeasible, particularly under partial a

Improving MLLM Training Efficiency via Stage-Aware Sparsity

arXiv:2509.18150v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated outstanding performance across a variety of domains. However, training MLLMs is oft

InvDesFlow-AL: active learning-based workflow for inverse design of functional materials

arXiv:2505.09203v2 Announce Type: replace-cross Abstract: Developing inverse design methods for functional materials with specific properties is critical to advancing fields like renewable energy, cat

tutorialsarxiv-cs-ai

Applications

Isolating Nonlinear Independent Sources in fMRI with eta-TCVAE Models

arXiv:2605.16708v1 Announce Type: new Abstract: Learning meaningful latent representations from nonlinear fMRI data remains a fundamental challenge in neuroimaging analysis. Traditional independent co

applicationsarxiv-cs-lg

Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits

arXiv:2602.15405v2 Announce Type: replace Abstract: Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancem

tutorialsarxiv-cs-lg

Language Game: Talking to Non-Human Systems

model-releasesarxiv-cs-lg

arXiv:2605.16321v1 Announce Type: new Abstract: Language carries thought and coordination among humans but rarely reaches further along the spectrum of diverse intelligence. Yet non-neural systems --

Learning-Based Adaptive Control for Surgical Robotic Exposure Task on Deformable Tissues

arXiv:2605.17927v1 Announce Type: new Abstract: In various surgical procedures, regions of interest (ROIs) such as organs or lesions are often occluded by overlying tissues, requiring surgeons to achi

safetyarxiv-cs-ro

Learning to Look Benign: Targeted Evasion of Malware Detectors via API Import Injection

arXiv:2605.18624v1 Announce Type: cross Abstract: Machine learning-based malware detectors are widely deployed in antivirus and endpoint detection systems, yet their reliance on static features makes

Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains

arXiv:2605.17359v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems have shown strong potential for complex reasoning by coordinating specialized agents through struct

safetyarxiv-cs-cl

Learning Variable-Length Tokenization for Generative Recommendation

arXiv:2605.17779v1 Announce Type: new Abstract: Generative recommendation reformulates recommendation as next-token prediction over discrete semantic identifiers (IDs). A fundamental yet unexplored de

LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbots

arXiv:2605.16474v1 Announce Type: cross Abstract: The integration of advertising auction mechanisms into large language model (LLM)-based chatbots presents a significant opportunity for commercializat

LLM-Based Intelligent Notification Composition: From Static Personalization to Context-Aware Persuasive Messaging

arXiv:2605.16264v1 Announce Type: cross Abstract: Push notifications remain among the most direct channels through which digital platforms engage users, yet existing approaches have invested heavily i

tutorialsarxiv-cs-cl

Long-horizon prediction of three-dimensional wall-bounded turbulence with CTA-Swin-UNet and resolvent analysis

arXiv:2605.17888v1 Announce Type: cross Abstract: Long-horizon prediction of three-dimensional (3D) wall-bounded turbulence with machine-learning methods remains a challenging task, due to the rapid a

Longwang: Zero-Shot Global Spatiotemporal Precipitation Downscaling with a Latent Generative Prior

arXiv:2605.17603v1 Announce Type: cross Abstract: High-resolution precipitation information is essential for climate impact assessment, yet global climate models remain too coarse to resolve key small

Lost or Hidden? A Concept-Level Forgetting in Supervised Continual Learning

arXiv:2605.16374v1 Announce Type: cross Abstract: Continual learning studies how models can adapt to new tasks while retaining previously acquired knowledge. Although a broad spectrum of methods has b

researcharxiv-cs-ai

M^2FedAQI: Multimodal Federated Learning for Air Quality Prediction on Heterogeneous Edge Devices

model-releasesarxiv-cs-lg

arXiv:2605.16375v1 Announce Type: new Abstract: Accurate air quality prediction is essential for public health, environmental monitoring, and industrial safety. However, most existing approaches rely

MANTA: Multi-turn Assessment for Nonhuman Thinking & Alignment

arXiv:2605.16301v1 Announce Type: cross Abstract: Single-turn benchmarks such as AnimalHarmBench (AHB) have established important baselines for measuring animal welfare alignment in large language mod

Markerless Motion Capture for Biomechanical Whole-Body Kinematic Estimation in Infants

arXiv:2605.17120v1 Announce Type: new Abstract: arly identification of motor impairment in infancy relies on expert visual assessment of spontaneous movement, motivating the development of automated,

researcharxiv-cs-cv

Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting

arXiv:2605.17091v1 Announce Type: new Abstract: Scientific forecasting typically relies on direct state prediction, an approach that grows brittle under data scarcity, extended horizons, non-stationar

MedMIX: Modality-Internal Expert Fusion for Multimodal Medical Diagnosis

arXiv:2605.16639v1 Announce Type: new Abstract: Multimodal clinical prediction faces three challenges: multiple foundation models (FMs) with complementary strengths per modality, pervasive missing mod

MirrorBench: A Benchmark to Evaluate Conversational User-Proxy Agents for Human-Likeness

arXiv:2601.08118v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as human simulators, both for evaluating conversational systems and for generating fine-tuning da

Monocular Open Vocabulary Occupancy Prediction for Indoor Scenes

arXiv:2602.22667v2 Announce Type: replace Abstract: Open-vocabulary 3D occupancy is vital for embodied agents, which need to understand complex indoor environments where semantic categories are abunda

MorphSeek: Fine-grained Latent Representation-Level Policy Optimization for Deformable Image Registration

arXiv:2511.17392v3 Announce Type: replace Abstract: Deformable image registration (DIR) remains a fundamental yet challenging problem in medical image analysis, largely due to the prohibitively high-d

Multi-Mode Quantum Annealing for Generative Representation Learning with Boltzmann Priors

arXiv:2604.00919v2 Announce Type: replace-cross Abstract: Energy-based models provide a natural bridge between statistical physics and machine learning by representing data through structured energy l

Noise2Params: Unification and Parameter Determination from Noise via a Probabilistic Event Camera Model

arXiv:2605.16317v1 Announce Type: new Abstract: Accurate, unified models for event cameras (ECs) remain elusive, hampering calibration and algorithm design. We develop a foundational probabilistic mod

Old Habits Die Hard: How Conversational History Geometrically Traps LLMs

arXiv:2603.03308v2 Announce Type: replace-cross Abstract: How does the conversational past of large language models (LLMs) influence their future performance? Recent work suggests that LLMs are affect

OmniCode: A Benchmark for Evaluating Software Engineering Agents

arXiv:2602.02262v3 Announce Type: replace-cross Abstract: LLM-powered coding agents are redefining how real-world software is developed. To drive the research towards better coding agents, we require

Online Algorithms with Unreliable Guidance

arXiv:2602.20706v2 Announce Type: replace Abstract: This paper introduces online algorithms with unreliable guidance (OAG), a model for ML-augmented online decision-making that cleanly separates the p

tutorialsarxiv-cs-ai

Agents

ORION: Option-Regularized Deep Reinforcement Learning for Cooperative Multi-Agent Online Navigation

arXiv:2601.01155v3 Announce Type: replace Abstract: Existing methods for multi-agent navigation typically assume fully known environments, offering limited support for partially known scenarios with o

agentsarxiv-cs-ro

Local Ai

Overcoming the Intrinsic Performance Limitations of MEMS IMU via Diffusion-Based Generative Learning

arXiv:2605.16391v1 Announce Type: cross Abstract: Inertial measurement units (IMUs) are fundamental sensing components in multi-source integrated navigation systems, and their performance directly det

local-aiarxiv-cs-ai

Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign

arXiv:2605.16452v1 Announce Type: cross Abstract: Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiog

Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehicles

arXiv:2605.16858v1 Announce Type: cross Abstract: Autonomous Vehicles (AVs) must make reliable decisions in dense urban environments where pedestrian behavior is variable, sometimes abnormal, and ofte

Agents

PersonaArena: Dynamic Simulation for Evaluating and Enhancing Persona-Level Role-Playing in Large Language Models

arXiv:2605.17044v1 Announce Type: new Abstract: Large language models (LLMs) increasingly serve as interactive social agents, yet their ability to maintain coherent and authentic persona-level role-pl

agentsarxiv-cs-ai

Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry

arXiv:2605.16325v1 Announce Type: cross Abstract: Phase-transition phenomena in deep learning (grokking, emergent capabilities, and ontological reorganization under context shift) have been studied th

Pointwise Generalization in Deep Neural Networks

arXiv:2605.18598v1 Announce Type: new Abstract: We address the fundamental question of why deep neural networks generalize by establishing a pointwise generalization theory for fully connected network

safetyarxiv-cs-lg