Search: “models”

I-BFM: Reward-Conditioned Robust Humanoid Interaction via Unsupervised Reinforcement Learning

arXiv:2610.06129v1 Announce Type: new Abstract: Behavioral foundation models (BFMs) have recently shown that a single humanoid policy can support diverse whole-body control, but extending such general

safetyarxiv-cs-ro

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IGA-KAN: Isogeometric Analysis with Physics-Informed Closed-Form Kolmogorov-Arnold Networks for Forward and Inverse PDEs

DGX agent

arXiv:2610.06348v1 Announce Type: cross Abstract: Isogeometric analysis (IGA) solves partial differential equations accurately on exact NURBS geometry, whereas neural solvers are mesh-free but often o

local-aiarxiv-cs-lg

6 Oct 2026

Improving Forecasts of Suicide Attempts for Patients with Little Data

arXiv:2511.18199v2 Announce Type: replace-cross Abstract: Ecological Momentary Assessment (EMA) studies provide real-time data on suicidal thoughts and behaviors, but forecasting suicide attempts rema

Joint Precision Neural Networks: Task-Aware Dependency and Predictive Learning

arXiv:2610.06023v1 Announce Type: new Abstract: Exploiting meaningful latent structures from data to solve downstream tasks is a fundamental challenge in signal processing and machine learning. While

applicationsarxiv-cs-lg

Large Stepsizes Federated Learning on Logistic Regression with Linearly Separable Data: The Case of Heterogeneous Devices

arXiv:2610.05915v1 Announce Type: new Abstract: This paper revisits the distributed learning problem for training a multinomial logistic regression model with the Federated Averaging (exttt{FedAvg}) a

Learning Conditional Source Distribution via Flow Reversal for Temporal Flow Matching

arXiv:2610.05349v1 Announce Type: new Abstract: We introduce CNP-Flow, a flow matching framework for temporal generation that learns conditional source distributions through flow reversal. Whereas sta

Tutorials

Learning Subject-Specific Anatomical Representations via Manifold Expansion: Application to Accelerated Multi-Contrast MRI

arXiv:2610.04028v1 Announce Type: new Abstract: Clinical MRI routinely acquires multiple contrast-weighted images of the same anatomy for complementary tissue characterization. However, current accele

tutorialsarxiv-cs-cv

Learning While Scheduling Jobs under Context-Dependent Service Rates: An Anytime Rate-Optimal Algorithm

arXiv:2610.06006v1 Announce Type: new Abstract: We study contextual queueing bandits, where a learner schedules jobs while learning unknown service rates modeled by logistic functions of job-server fe

Length Generalization Needs Proper Regularization

arXiv:2610.04518v1 Announce Type: new Abstract: Length generalization is the ability of sequential models to perform well on context lengths unseen during training. In this work, we show that the chal

Agents

Level-of-Token Diffusion

arXiv:2610.05816v1 Announce Type: new Abstract: Image and video diffusion models allocate equal computation to every region, even when the intended scene calls for varying levels of detail. The spatia

agentsarxiv-cs-cv

Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks

arXiv:2610.03741v1 Announce Type: cross Abstract: Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks becaus

Long-MDR: Long-Context Reinforcement Learning for Multimodal Deep-Research Agents

arXiv:2610.05195v1 Announce Type: new Abstract: The next generation of multimodal research agents must reason over long-lived research histories rather than short model completions. During a single ta

MagServo: Uncertainty-Resilient Hierarchical Magnetic Servoing via Learned Latent Representations

arXiv:2610.06046v1 Announce Type: new Abstract: Magnetic navigation provides contact-free and line-of-sight-independent feedback for robotic systems, yet existing approaches typically rely on explicit

researcharxiv-cs-ro

Multimodal Deep Survival Analysis for Sinkhole Susceptibility

arXiv:2610.06365v1 Announce Type: new Abstract: Sinkholes are a widespread geohazard in karst terrain. In Florida, soluble carbonate bedrock, shallow groundwater, and intense rainfall combine to make

applicationsarxiv-cs-lg

Operational Abstractions of Neural Network Concepts via Topological Representations

arXiv:2610.05017v1 Announce Type: new Abstract: Concept-based methods provide a semantic level for interpreting and manipulating learned representations, but existing editing approaches are typically

Tutorials

Pay to Learn, Share to Earn: Incentivized Federated Multi-Player Bandits

arXiv:2610.06062v1 Announce Type: new Abstract: Federated multi-player multi-armed bandit problems model collaborative sequential decision-making where multiple players interact with a common bandit e

tutorialsarxiv-cs-lg

PIT-GCL: Protein Interaction using Topological Graph Contrastive Learning

arXiv:2610.04850v1 Announce Type: new Abstract: Protein binding prediction is central to target identification, therapeutic binder design, and large scale screening, yet remains challenging because bi

Reachability-Aware Diffusion Policy Optimization

arXiv:2610.05969v1 Announce Type: new Abstract: Diffusion policies provide expressive action distributions for continuous-control reinforcement learning. However, safety-aware online diffusion policy

REFLEX: Reflective Evolution from LLM Experience

arXiv:2606.16496v2 Announce Type: replace-cross Abstract: Large multimodal language models (MLLMs) have emerged as powerful tools for guiding evolutionary search toward interpretable programmatic poli

ReMem: Streaming Video Understanding With Long Context Retention

arXiv:2610.05940v1 Announce Type: new Abstract: Despite their impressive performance on a wide range of video understanding tasks, current Vision Language Models (VLMs) are predominantly designed for

ResOPD: Tail Residualization for Sparse On-Policy Distillation

arXiv:2610.04882v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model on self-generated trajectories, but transmitting dense teacher distributions across long reasoning t

Hardware

Rethinking Least-Core Computation in Contextual-Distractor Games

arXiv:2610.06087v1 Announce Type: new Abstract: Game-theoretic attribution explains a model by assigning credit to its features or training examples. The least core has attracted interest as an altern

hardwarearxiv-cs-lg

SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting

arXiv:2610.04109v1 Announce Type: new Abstract: Real-world time series are frequently driven by exogenous events and structural shifts, rendering conventional forecasting based solely on historical nu

SoundWeaver: Compositional Warm-Starting for Text-to-Audio Diffusion Serving

arXiv:2603.07865v2 Announce Type: replace-cross Abstract: Text-to-audio (T2A) diffusion models generate high-quality audio but require tens of neural function evaluations (NFEs), resulting in substant

StepCAD: Mesh-to-CAD Code Generation via LLM Policy and Geometry-Guided Search

arXiv:2610.03799v1 Announce Type: new Abstract: Recovering executable CAD programs from 3D meshes is challenging due to the compositional nature of CAD construction and the interaction between discret

T-JEPA: A Temporal Joint-Embedding Predictive Architecture for Learning Better Remote Sensing Representations

arXiv:2610.05731v1 Announce Type: new Abstract: Earth observation (EO) data provide rich temporal supervision, yet existing remote sensing foundation models mainly exploit sequential observations thro

Terrain-Dependent Intra-Cycle Leg Timing for Effective Locomotion on Granular Slopes

arXiv:2610.04144v1 Announce Type: new Abstract: Locomotion on granular slopes such as sand dunes remains a fundamental challenge for legged robots due to reduced shear strength and gravity-induced ani

researcharxiv-cs-ro

The Blind Spot Paradox: When Adaptive Classifiers Defeat Drift Detectors

arXiv:2610.05853v1 Announce Type: new Abstract: Monitoring concept drift from an adaptive classifier's error stream creates an operational conflict with the model's own update loop. When internal adap

TIMBRE: Teaching Time Series Forecasters to Read, Remember, and Reconcile

arXiv:2610.04795v1 Announce Type: new Abstract: Event-informed forecasting requires translating reports and historical responses into changes to a numerical forecast. We propose TIMBRE (Temporal Integ

Transform Trained Transformer for Accelerating Native 4K Video Generation

arXiv:2512.13492v2 Announce Type: replace Abstract: Native 4K (2176imes3840) video generation remains a critical challenge due to the quadratic computational explosion of full-attention as spatiotempo

Two Americas of Well-Being: Divergent Rural-Urban Patterns of Life Satisfaction and Happiness from 2.6 B Social Media Posts

arXiv:2511.10542v2 Announce Type: replace-cross Abstract: Using 2.6 billion geolocated social-media posts (2014-2022) and a fine-tuned generative language model, we construct county-level indicators o

Underscoring the Problem: Why Softpick Fails at Initialization

arXiv:2610.05488v1 Announce Type: new Abstract: Softmax attention gives every token a nonzero weight, which in trained models concentrates into attention sinks and massive activations that widen the d

Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

arXiv:2610.05425v1 Announce Type: new Abstract: Automated checks of radiology reports may rely on AI-generated checklists that leave findings unmentioned. We used reinforcement learning to train a vis

Tutorials

Variance-Optimal Control Variates for Learning with Black-box Feedback

arXiv:2610.04766v1 Announce Type: new Abstract: Modern models increasingly learn through black-box oracles such as humans, optimization solvers, and external tools that provide feedback without exposi

tutorialsarxiv-cs-lg

Video Replanning via Latent Embedding Refinement and Rejection-Based Sampling

arXiv:2510.17315v3 Announce Type: replace Abstract: Video planning has emerged as a flexible framework for robot manipulation, in which a generative model predicts a video of task completion, and a do

applicationsarxiv-cs-ro

Where Does Jagged Competence Come From?

arXiv:2610.03831v1 Announce Type: new Abstract: Capable systems often show jagged competence: low average error alongside failures on particular inputs. We ask where it comes from in a task built from

ZeST: an VLM-based Zero-Shot Traversability Navigation for Unknown Environments

arXiv:2508.19131v3 Announce Type: replace-cross Abstract: The advancement of robotics and autonomous navigation systems hinges on the ability to accurately predict terrain traversability. Traditional

Agents

A Simulation-Grounded Agentic VLM Framework for Wildfire Monitoring and Reporting

arXiv:2610.02451v1 Announce Type: new Abstract: Effective wildfire monitoring requires relating visual evidence to physical fire dynamics, yet real videos with synchronized physical annotations are sc

agentsarxiv-cs-cv

A Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News

arXiv:2511.18618v2 Announce Type: replace-cross Abstract: In our daily lives, newspapers are an essential information source that impacts how the public talks about present-day issues. However, effect

researcharxiv-cs-ai

A Unified Framework for Empowerment and Predictive Control

arXiv:2610.03563v1 Announce Type: new Abstract: Sampling-based model predictive control (MPC) is a powerful approach to trajectory optimization, but its performance depends on an informative cost func

safetyarxiv-cs-ro

Agents

AgentTrap: Stateful Feedback Deception against Autonomous Penetration Testing Agents

arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def

agentsarxiv-cs-ai

AMBER: Multi-View Adaptive Budget Allocation for Listwise Vision-Language Reranking

arXiv:2610.02831v1 Announce Type: new Abstract: Vision-language models (VLMs) are powerful listwise rerankers for multimodal retrieval, but high inference costs restrict them to evaluating small local

researcharxiv-cs-ai

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions

arXiv:2506.05766v2 Announce Type: replace Abstract: Retrieval augmented generation (RAG) has shown great power in improving Large Language Models (LLMs). However, most existing RAG-based LLMs are dedi

applicationsarxiv-cs-cl

Can We Trust LLMs on Memristors? Diving into Reasoning Ability under Non-Ideality

arXiv:2603.13725v2 Announce Type: replace Abstract: Memristor-based analog compute-in-memory (CIM) architectures provide a promising substrate for the efficient deployment of Large Language Models (LL

researcharxiv-cs-cl

Capability Scaling-Down Laws for LLM Compression

arXiv:2610.02462v1 Announce Type: cross Abstract: LLM compression reduces inference costs and memory requirements, but selecting a method and configuration remains largely empirical because comparable

researcharxiv-cs-cl

CoMemNet: A Continual Memory Network with Drift-Aware Sampling for Traffic Prediction

arXiv:2605.05738v2 Announce Type: replace-cross Abstract: Traffic sensor networks evolve as sensors are added and traffic distributions change, whereas most forecasting models assume a fixed node set

researcharxiv-cs-ai

Confidence-Controlled XAI Auditing for Pedestrian Detection under Domain Shift

arXiv:2610.02364v1 Announce Type: new Abstract: Explainability is increasingly required for perception models in intelligent vehicles, yet whether explanations remain faithful under driving domain shi

Local Ai

Cordial Learning: Distributed Training with Correlated Data

arXiv:2610.03330v1 Announce Type: cross Abstract: We consider a distributed learning task with agents that have correlated data. Specifically, the label of an agent depends on the input of other agent

local-aiarxiv-cs-ai