Where Has the Foreign Signal Gone?
We compare the relation between sentiment noise in the Twitter feed and losses for stocks of domestic and foreign firms. The mean quarterly domestic-foreign difference in the slope of next-quarter…
computer-vision
MLINFO COLLECTION
製造業の異常検知
センサ時系列、画像検査、予測保全、異常スコアリングに使えるAI技術を整理します。
記事一覧
34 / 37Reasoning as a Distribution: Generative Plan Latents for Vision-Language-Action Models
Vision-Language-Action (VLA) policies increasingly reason before acting, but existing reasoning models compress this intermediate decision into a single representation. When several plans are valid,…
nlp
De-Diffusing WAMs: Action-Sufficient Direct Prediction for Robot Control
Cascade world-action models (WAMs) use predicted visual futures to condition robot actions, but inherit costly iterative inference from diffusion-pretrained experts. We ask what a single-step…
deep-learning
FIT-MAC: A Closed-Loop Multi-Agent Framework for Robust Vision-Language-Action Models
Vision-language-action (VLA) models have achieved strong performance on standard robotic manipulation benchmarks. However, their reliability can degrade substantially when task conditions deviate…
computer-vision
Temporal Difference Learning of Probabilistic Reach-Avoid Value Functions
Reach-avoid sets, defining the states from which a task can be completed while avoiding unsafe regions, are fundamental tools for deploying robots in environments subject to disturbances and…
computer-vision
When Does Training on Synthetic Data Provably Work?
High-quality training data are a major bottleneck in machine learning, motivating increasing use of artificially generated data. We study when a binary classifier trained on synthetic data transfers…
computer-vision
PACT-VLA: Speculative Action-Chunk Verification with Pre-Commit Observations
Vision-language-action (VLA) policies are commonly deployed with asynchronous inference in real-world settings, where the next action chunk is generated while the robot is still executing the…
nlp
Learning Tactile-Aware Hand Representations from Human Hand-Object Interaction Data
Tactile representation learning for dexterous manipulation often requires substantial robot-side data collection, limiting its scalability across different hands and sensors. We explore whether…
machine-learning
EventSync: Event-Driven Memory Updates for History-Dependent Manipulation
History-dependent robotic manipulation requires task context and interaction history, as the current observation alone is insufficient to determine the next action. Hierarchical frameworks use task…
deep-learning
What Novice Operators See Changes What the Policy Learns: A User Study of Keypoint Hand Visual Representation for Teleoperated Demonstration
Imitation learning increasingly relies on novice operators, whose demonstrations fall short of experts' in number and inter-trial consistency. Operators act on what they are shown, yet how the…
computer-vision
Give the Model a Finger: Developmentally Aligned Evaluation of Counting in Vision-Language Models
Vision-language models (VLMs) are exact on small sets and drift into estimation on larger ones, a profile reminiscent of children before they master counting. Children cross the barrier with…
computer-vision
CovNav: Conformal Prediction-Guided Adaptive Inference for Object Goal Navigation
In object goal navigation (ObjectNav), an embodied agent must find a target object (e.g., "find a bed") in a previously unseen environment, relying on spatial commonsense such as object…
nlp
PLaCA: Learning Patch-Level Future Latent Change for Action Generation
Vision-Language-Action (VLA) models generate robot actions from visual observations and language instructions, but effective manipulation also requires anticipating how the environment will change.…
nlp
Active Pilot Sampling for Multi-fidelity Estimation in Stochastic Optimization
Stochastic optimization with high-fidelity nonlinear models is often computationally prohibitive because each objective evaluation requires sampling-based uncertainty quantification inside an outer…
computer-vision
StratFL: Countering Covert Model Poisoning Attacks with Strategic Federated Learning
Advanced persistent threats (APTs) are a major concern in federated learning (FL) deployments in critical sectors such as healthcare, and finance. Traditional defense mechanisms fail to contain APTs…
computer-vision
Explore Once, Evaluate Many: Multiple Policy Evaluation for Stochastic Linear Bandits
We study how to evaluate $K$ target policies simultaneously in stochastic contextual bandits with linear reward structure. Given a known $d$-dimensional feature map and reward-free access to policy…
computer-vision
Why Alternation Speeds Up Counterfactual Regret Minimization?
Solving imperfect-information games at scale rests on counterfactual regret minimization with the regret matching$^{+}$ (RM$^{+}$) update, and a seemingly minor implementation choice accounts for…
computer-vision
The Tilted Sampling Problem: Optimism, Posterior Sampling, and Logarithmic Regret
Many modern learning systems are used not to select a single best action, but to sample diverse high-quality outputs. Examples include entropy-regularized reinforcement learning, RLHF, and…
computer-vision
Robust Covariance Estimation for Entry-wise Contaminated and Partially Observed Data via Expectation Maximization Algorithm
Robust covariance estimation under entry-wise contamination and missing data is challenging in various signal processing applications. Under the Student-$t$ model, observation-level reweighting…
computer-vision
Conditional Mean Flows: Few-Step Densities for Simulation-Based Inference
Flow matching has emerged as a powerful generative family for simulation-based inference (SBI). However, sampling and density evaluation require numerical integration at inference time.
computer-vision
Diffusion Score Estimation with Shallow Neural Networks: Regularity, Approximation, and Finite-Sample Rates
We study the sample complexity of estimating Ornstein--Uhlenbeck diffusion scores in $\mathbb R^d$ using denoising score matching (DSM) with finite-width shallow ReLU networks, and its implications…
computer-vision
Gaussian Approximation of Besov Functions for Logistic Classification on Manifolds
We study Gaussian kernel approximation and regularized logistic classification on a connected compact smooth embedded manifold $X\subset\mathbb R^d$ without boundary and of intrinsic dimension…
computer-vision
Cross-Fitting for Neural Posterior Estimation
Neural Posterior Estimation (NPE) fits an amortized conditional density estimator to a simulated training set of complete-data realizations. NPE's training objective, log-likelihood, favors posterior…
computer-vision
WhatIf-Bench: Benchmarking Intervention-Aware Time Series Forecasting
Recent time series foundation models (TSFMs) can consume covariates in-context, extending zero-shot forecasting to problems driven by external factors. This enables scenario analysis: forecasting how…
nlp