#robustness

try —

35 papers match

cs.CE2026

CoLAS: Multimodal Corroboration of Latent Asset Signals for Financial Trading

Yanzheng Jin, Pengyang Shao, Xiaohao Liu +3

CoLAS is a multimodal learning framework that extracts trading signals by identifying and reinforcing shared information across price data, news, and sentiment, improving robustnes…

#multimodal learning#financial trading#stock prediction#cryptocurrency
stat.ML2026

The Noise Premium in Adversarial Training for Kernel Regression

Yiling Xie, Xiaoming Huo

The paper analyzes adversarial training within reproducing kernel Hilbert spaces, deriving generalization bounds and showing how noise affects the trade‑off between robustness and…

#adversarial training#kernel methods#generalization#nonparametric learning
math.AT2026

Interval Decompositions for Multipersistence Modules over Finite Posets and Robustness of Sheaf Data on Simplicial Complexes

Pablo Hernández-García, Daniel Hernández Serrano, Darío Sánchez Gómez

The paper establishes conditions under which multipersistence modules indexed by finite posets can be broken down into direct sums of interval modules, and applies these results to…

#multipersistence#interval decomposition#cellular sheaves#simplicial complexes
eess.SY2026

A subspace approach to data-driven predictive control for linear parameter-varying systems

Federico Porcari, Chris Verhoek, Valentina Breschi +2

The paper proposes a subspace-based data‑driven predictive control scheme for linear parameter‑varying (LPV) systems that avoids explicit model identification and offers reduced co…

#lpv systems#data-driven control#predictive control#subspace methods
cs.CL2026

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models

Parishruthi Ganesh, Gerry Dozier, Cheryl Seals

The paper systematically evaluates 41 open-weight language models for zero‑shot intent classification across multiple datasets, analyzing accuracy, calibration, robustness, and dep…

#intent classification#zero-shot learning#language model evaluation#instruction tuning
cs.AI2026

Beyond the Bidirectional Promise: Re-evaluating the Robustness of Diffusion Language Models

Saurabh Yadav, Badri Narayana Patro, Vijay Srinivas Agneeswaran

The paper evaluates how diffusion-based language models handle noisy inputs and adversarial attacks compared to traditional autoregressive models, finding that while they resist ce…

#diffusion language models#robustness#adversarial attacks#calibration