Search: “papers”

A hybrid analytical-PINN model for subsurface simulation of geothermal heat exchangers in heterogeneous underground

arXiv:2607.12271v1 Announce Type: new Abstract: In this paper, a parametric physics-informed neural network for solving the heterogeneous soil thermal problem with borehole heat exchangers (BHEs) as s

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HPC-Enabled Video-based Coastal Wave Parameter Estimation Using V-JEPA and Deep Spatiotemporal Learning

DGX agent

arXiv:2607.11998v1 Announce Type: cross Abstract: High deployment cost, poor spatial coverage and susceptibility to storm conditions are all challenges faced by traditional in-situ methods. This paper

model-releasesarxiv-cs-ai

15 Jul 2026

Image Matching Filtering and Refinement by Planes and Beyond

model-releasesarxiv-cs-cv

arXiv:2411.09484v5 Announce Type: replace Abstract: This paper provides a consistent and extensive evaluation of state-of-the-art filtering and refinement methods on common image matching pipelines. U

Knowledge- and Gradient-Guided Reinforcement Learning for Parametrized Action Markov Decision Processes

arXiv:2607.12924v1 Announce Type: new Abstract: In this paper, we study Reinforcement Learning in Parametrized Action Markov Decision Processes (PAMDP), where each decision consists of a symbolic acti

LQG solution for POMDP without estimating states: A minimum variance approach

arXiv:2607.12135v1 Announce Type: cross Abstract: This paper investigates the control of discrete-time linear time-invariant (LTI) systems subject to incomplete and corrupted measurements. Specificall

researcharxiv-cs-ro

Reducing information dependency does not cause training data privacy. Adversarially non-robust features do

arXiv:2607.12354v1 Announce Type: new Abstract: In this paper, we challenge the prevailing view that information dependency (including rote memorization) drives training data exposure to image reconst

Solution of the Hempel's statistical ambiguity problem and Causal AI

arXiv:2607.12826v1 Announce Type: new Abstract: This paper addresses Carl Hempel's longstanding problem of statistical ambiguity in inductive-statistical inference, in which contradictory predictions

Some Complexity Results for Robustness Verification for Binarized Neural Networks

arXiv:2606.18918v2 Announce Type: replace Abstract: This paper studies the computational complexity of verification problems for Binarized Neural Networks (BNNs), where activations (and sometimes weig

StratMamba: Strategic and Reactive Stream Partitioning for Path-Efficient LiDAR-Based Obstacle Avoidance

arXiv:2607.12370v1 Announce Type: new Abstract: This paper proposes StratMamba, a dual-stream Mamba-based temporal modeling architecture, to more efficiently capture long-horizon temporal dependencies

safetyarxiv-cs-ro

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial

Win by Silence: Deletion Non-Monotonicity, Autonomous Exploitation, and Typed-State Gating in LLM Plan Evaluation

arXiv:2607.12986v1 Announce Type: new Abstract: Plan evaluators can reward a strategic plan for becoming less explicit. This paper studies that failure in a staged expected-value scorer for LLM-genera

// An Anatomy of CLI Coding Agent Trajectories // (bookmark it) When your coding agent fails a task, when did the run actually go wrong? Mos…

// An Anatomy of CLI Coding Agent Trajectories // (bookmark it) When your coding agent fails a task, when did the run actually go wrong? Most reliability studies use the final label to answer this. Th

agentsdair-ai--x

13 Jul 2026

A First-Principles Theory of Slow Thinking and Active Perception

arXiv:2607.08196v1 Announce Type: new Abstract: As part of a series on first-principles modeling of cognitive functions, this paper attempts to provide a mathematical formulation of thinking and perce

safetyarxiv-cs-ai

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing

arXiv:2607.08177v1 Announce Type: new Abstract: In this paper, we study the automatic schema generation problem: given a collection of historical ship maintenance and operational reports across multip

Behavioral Privacy Leakage in Agentic Negotiation: Formalizing and Mitigating Inference Attacks via Randomized Policies

This paper was accepted at the AI4TCI (Workshop on AI for Secure and Trustworthy Critical Infrastructure Systems) Workshop at the International Conference on Availability, Reliability and Security (AR

agentsapple-ml-research

Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

model-releasesarxiv-cs-cl

arXiv:2607.08208v1 Announce Type: new Abstract: This paper describes our self-designed system for Task 1 of the MLC-SLM 2026 Challenge for multilingual two-speaker conversational speech. The system co

Distributed Sketching on Data Partitions for OLS Regression

arXiv:2607.07888v1 Announce Type: new Abstract: This paper studies distributed sketching for ordinary least squares (OLS) regression, an approach that distributes small sketches of a large data set ov

DocMaster: A Hierarchical Structure-Aware System for Document Analysis

arXiv:2607.08539v1 Announce Type: cross Abstract: Leveraging large language models (LLMs) to analyze complex documents -- such as academic papers, technical manuals, and financial reports -- has emerg

Douglas-Rachford Splitting for Group-Sparse Feedback Linear-Quadratic Control

arXiv:2507.19895v4 Announce Type: replace-cross Abstract: In this paper, we study the distributed linear quadratic problem with fixed communication topology (DFT-LQ) and the sparse feedback linear qua

Effective Gaussian Management for High-fidelity Scene Reconstruction

arXiv:2509.12742v4 Announce Type: replace Abstract: This paper proposes an effective Gaussian management framework for high-fidelity scene reconstruction of both appearance and geometry. Unlike recent

researcharxiv-cs-cv

fog: Expressing Motion and Emotion through Function Composition of AI-Generated Code

arXiv:2607.07952v1 Announce Type: cross Abstract: Motion and emotion are core parts of intelligent, expressive behavior. In this paper, we introduce fog, a function composition framework for implement

researcharxiv-cs-cl

Applications

(heta_l, heta_u)-Parametric Multi-Task Optimization: Joint Search in Solution and Infinite Task Spaces

arXiv:2503.08394v5 Announce Type: replace-cross Abstract: Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering

applicationsarxiv-cs-lg

Applications

Incredibly annoying when Fable has a forbidden thought in the middle of a long-running project and kills it. Apparently this page of referen…

applicationsethan-mollick--x

Incredibly annoying when Fable has a forbidden thought in the middle of a long-running project and kills it. Apparently this page of references in one of my papers makes Fable wonder about something t

Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs

arXiv:2310.07895v2 Announce Type: replace Abstract: This paper presents a method to efficiently classify the gastroenterologic section of images derived from Video Capsule Endoscopy (VCE) studies by e

Provably Optimal Learning Algorithms for Assistance Games

arXiv:2607.08012v1 Announce Type: cross Abstract: This paper studies an online variant of the assistance games framework, where an informed agent and an uninformed agent repeatedly interact over T tim

Statistical Efficiency and Inference of Quantile Distributional Reinforcement Learning

arXiv:2607.08444v1 Announce Type: cross Abstract: In this paper, we study quantile-based distributional reinforcement learning from the perspective of statistical efficiency. We focus on distributiona

safetyarxiv-cs-lg

Structured Pruning of Large Language Models via Power Transformation and Sign-Preserving Score Aggregation with Adaptive Feature Retention

arXiv:2607.08027v1 Announce Type: cross Abstract: This paper proposes an improved structured pruning method for large language models (LLMs) that addresses key challenges in adapting Adaptive Feature

Applications

Unpaired Joint Distribution Modeling via Multi-Scale Image Representations

arXiv:2607.08198v1 Announce Type: new Abstract: This paper studies the problem of learning a joint distribution from marginal observations, which is inherently ill-posed due to the ambiguity of feasib

applicationsarxiv-cs-cv

AirPASS: Over-the-Air Federated Learning via Pinching Antenna Systems

arXiv:2607.06768v1 Announce Type: cross Abstract: This paper investigates over-the-air federated learning (AirFL) in wireless systems where the access point is equipped with a multi-waveguide pinching

Bound to Disagree: Generalization Bounds via Certifiable Surrogates

arXiv:2602.23128v2 Announce Type: replace Abstract: Generalization bounds for deep learning models are typically vacuous, not computable or restricted to specific model classes. In this paper, we tack

Can Reinforcement Learning Efficiently Discover Price Manipulation?

arXiv:2607.06121v1 Announce Type: cross Abstract: In this paper, we investigate whether a model-free RL agent can identify and exploit price manipulation opportunities more effectively than a traditio

Diffusion enabled Optimal Transport distances for graph matching

arXiv:2607.06646v1 Announce Type: cross Abstract: This paper introduces Diffusion Semi-Relaxed Fused Gromov-Wasserstein (DsrFGW), a novel method for graph comparison that unifies node features and str

Hybrid Least Squares/Gradient Descent Methods for MIONets

arXiv:2607.06976v1 Announce Type: cross Abstract: In this paper, we propose an efficient hybrid least squares/gradient descent (LSGD) method for MIONets to accelerate training. This method generalizes

Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints

arXiv:2607.07136v1 Announce Type: new Abstract: This paper presents a Spatiotemporal Tube (STT)-based control framework for general unknown nonlinear Euler-Lagrange (EL) systems subject to input const

agentsarxiv-cs-ro

Macroeconomic Message Passing for Anticipating Foreign Exchange Regime Changes: A Deep Logical Learning Approach using Graph Tsetlin Machines

arXiv:2607.06719v1 Announce Type: cross Abstract: This paper introduces a graph-theoretic approach for predicting market regimes in foreign exchange (FX) currency prices. Specifically, the proposed mo

Nonlinear Bandit

model-releasesarxiv-cs-lg

arXiv:2607.07304v1 Announce Type: new Abstract: In this paper we first study the problem of generalized linear bandit (GLB) under heavy-tailed noise. The characteristics of heavy-tailed distributions

Physics-guided spatiotemporal neural models for fuel density prediction

arXiv:2607.06999v1 Announce Type: cross Abstract: This paper presents a physics-guided machine learning (PGML) framework for fuel density prediction, integrating physics constraints and domain knowled

ProMoE-FL: Prototype-conditioned Mixture of Experts for Multimodal Federated Learning with Missing Modalities

arXiv:2607.06633v1 Announce Type: cross Abstract: In this paper, we address the problem of multimodal federated learning with missing modality. Existing methods utilize an additional public dataset or

Tutorials

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection

arXiv:2607.07192v1 Announce Type: new Abstract: In this paper, we study Single-Domain Generalized Object Detection (Single-DGOD), which aims to transfer a detector trained on a single source domain to

tutorialsarxiv-cs-cv

RoboLight: A Dataset with Linearly Composable Illumination for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2603.04249v2 Announce Type: replace Abstract: In this paper, we introduce RoboLight, the first real-world robotic manipulation dataset capturing synchronized episodes under systematically varied

Towards a Pseudo-Labeling Workflow for Celltype-Classification from Explanted Brain Slice Recordings

arXiv:2607.06569v1 Announce Type: cross Abstract: This paper proposes an unsupervised workflow to pseudo-label extracellular spikes from human brain slice MEA recordings into two putative cell types:

safetyarxiv-cs-lg

Understanding Two-Layer Neural Networks with Smooth Activation Functions

arXiv:2507.14177v2 Announce Type: replace-cross Abstract: This paper aims to understand the training solution, which is obtained by the back-propagation algorithm, of two-layer neural networks whose h

Video-Based Detection of squint and cataract for accessibility-aware adaptive web interface rendering

arXiv:2607.07099v1 Announce Type: new Abstract: Squint and cataract are major ocular disorders that majorly affect visual perception and interaction capability. This paper proposes a real-time video-b

researcharxiv-cs-cv

Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation

arXiv:2607.05985v1 Announce Type: new Abstract: This paper presents a black-box evaluation framework to systematically assess the ability of Large Language Models (LLMs) to generate Design Structure M

Automated Compliance Mapping in Cloud Security with Domain-Adapted Sentence Transformers

arXiv:2607.06364v1 Announce Type: new Abstract: Mapping cloud security controls to technical metrics is currently a manual process. This paper proposes domain adaptation of Sentence Transformer models

researcharxiv-cs-cl

Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment

arXiv:2511.06229v3 Announce Type: replace Abstract: This paper focuses on dynamic origin-destination matrix estimation (DODE), a crucial calibration process necessary for the effective application of

safetyarxiv-cs-lg

Designing Maintainable Hybrid Generative Systems: A Quantum-Inspired Approach to Automated Music Harmony Generation

arXiv:2607.06296v1 Announce Type: cross Abstract: This paper presents the design and evaluation of a maintainable hybrid generative architecture for automated music harmony generation from melody. The

ikeabench

ikeabench Furniture assembly is the task everyone name-drops and nobody actually attempts at real scale. Every demo I have seen is a scaled down IKEA leg or a single arm on a toy chair. This paper doe

agentsyohei-nakajima--x