Expertini Research Research

Browse Research Papers

346,661+ open-access research outputs.

โœ• Clear
๐Ÿ” avoidance learning
Showing 346661 results for "avoidance learning"
Education Preprint PDF DOI

Multidimensional Profiles of Critical Thinking in Physics Labs: Latent Structure, Instructional Change, and Connections to Physics Identity

Marcus Kubsch, Natasha G. Holmes, Antti Lehtinen ยท 2026

The Physics Lab Inventory of Critical Thinking (PLIC) measures three components of students' critical thinking in physics labs: evaluating data, evaluating methods, and proposing next steps. Prior worโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Pt-wedge squeegee cleaning of two-dimensional materials and heterostructures

Emine Yegin, Doruk Pehlivanoglu, T. Serkan Kas{i}rga ยท 2026

The surface of ultra-thin materials plays a crucial role in determining the properties. This is particularly important in two-dimensional (2D) materials where the surface-bulk distinction is no longerโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Learning Robustness at Test-Time from a Non-Robust Teacher

Stefano Bianchettin, Giulio Rossolini, Giorgio Buttazzo ยท 2026

Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are scarce and unlabeled. While this paradigm has pโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

GeomPrompt: Geometric Prompt Learning for RGB-D Semantic Segmentation Under Missing and Degraded Depth

Krishna Jaganathan, Patricio Vela ยท 2026

Multimodal perception systems for robotics and embodied AI often assume reliable RGB-D sensing, but in practice, depth is frequently missing, noisy, or corrupted. We thus present GeomPrompt, a lightweโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Finetune Like You Pretrain: Boosting Zero-shot Adversarial Robustness in Vision-language Models

Songlong Xing, Weijie Wang, Zhengyu Zhao, Jindong Gu, Philip Torr, Nicu Sebe ยท 2026

Despite their impressive zero-shot abilities, vision-language models such as CLIP have been shown to be susceptible to adversarial attacks. To enhance its adversarial robustness, recent studies finetuโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

The Impact of Federated Learning on Distributed Remote Sensing Archives

Anand Umashankar, Karam Tomotaki-Dawoud, Nicolai Schneider ยท 2026

Remote sensing archives are inherently distributed: Earth observation missions such as Sentinel-1, Sentinel-2, and Sentinel-3 have collectively accumulated more than 5 petabytes of imagery, stored andโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

bacpipe: a Python package to make bioacoustic deep learning models accessible

Vincent S. Kather, Sylvain Haupert, Burooj Ghani, Dan Stowell ยท 2026

1. Natural sounds have been recorded for millions of hours over the previous decades using passive acoustic monitoring. Improvements in deep learning models have vastly accelerated the analysis of larโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Progressively Texture-Aware Diffusion for Contrast-Enhanced Sparse-View CT

Tianqi Wang, Wenchao Du, Hongyu Yang ยท 2026

Diffusion-based sparse-view CT (SVCT) imaging has achieved remarkable advancements in recent years, thanks to its more stable generative capability. However, recovering reliable image content and visuโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

UniToolCall: Unifying Tool-Use Representation, Data, and Evaluation for LLM Agents

Yijuan Liang, Xinghao Chen, Yifan Ge, Ziyi Wu, Hao Wu, Changyu Zeng, Wei Xing, Xiaoyu Shen ยท 2026

Tool-use capability is a fundamental component of LLM agents, enabling them to interact with external systems through structured function calls. However, existing research exhibits inconsistent interaโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale

Liujie Zhang, Benzhe Ning, Rui Yang, Xiaoyan Yu, Jiaxing Li, Lumeng Wu, Jia Liu, Minghao Li, Weihang Chen, Weiqi Hu, Lei Zhang ยท 2026

Reinforcement learning (RL) post-training has proven effective at unlocking reasoning, self-reflection, and tool-use capabilities in large language models. As models extend to omni-modal inputs and agโ€ฆ

Read Paper โ†’
Computer Science Preprint PDF DOI

Human Centered Non Intrusive Driver State Modeling Using Personalized Physiological Signals in Real World Automated Driving

David Puertas-Ramirez, Raul Fernandez-Matellan, David Martin Gomez, Jesus G. Boticario ยท 2026

In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding to take-over requests. Therefore, reliable driver โ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Eliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach

Haolin Li, Shuyang Jiang, Ruipeng Zhang, Jiangchao Yao, Ya Zhang, Yanfeng Wang ยท 2026

While large language models hold promise for complex medical applications, their development is hindered by the scarcity of high-quality reasoning data. To address this issue, existing approaches typiโ€ฆ

Read Paper โ†’
Computer Science Preprint PDF DOI

RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resilience

Hanbo Huang, Xuan Gong, Yiran Zhang, Hao Zheng, Shiyu Liang ยท 2026

Large language model (LLM) watermarking has emerged as a promising approach for detecting and attributing AI-generated text, yet its robustness to black-box spoofing remains insufficiently evaluated. โ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Obtaining Partition Crossover masks using Statistical Linkage Learning for solving noised optimization problems with hidden variable dependency structure

M.W. Przewozniczek, B. Frej, M.M. Komarnicki, M. Prusik, R. Tinos ยท 2026

In optimization problems, some variable subsets may have a joint non-linear or non-monotonical influence on the function value. Therefore, knowledge of variable dependencies may be crucial for effectiโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory

Weixian Waylon Li, Jiaxin Zhang, Xianan Jim Yang, Tiejun Ma, Yiwen Guo ยท 2026

Structured memory representations such as knowledge graphs are central to autonomous agents and other long-lived systems. However, most existing approaches model time as discrete metadata, either sortโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

A Systematic Study of Noise Effects in Hybrid Quantum-Classical Machine Learning

Bhavna Bose, Muhammad Faryad ยท 2026

Near-term quantum machine learning (QML) models operate in environments wherein noise is unavoidable, arising from both imperfect classical data acquisition and the limitations of noisy intermediate-sโ€ฆ

Read Paper โ†’
Mathematics Preprint PDF DOI

Decision-Aware Predictions for Right-Hand Side Parameters in Linear Programs

Jackson Forner, Miju Ahn, Harsha Gangammanavar ยท 2026

This paper studies an integrated learning and optimization problem in which a prediction model estimates the right-hand-side parameters of a linear program (LP) using a contextual vector. Considering โ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

SVD-Prune: Training-Free Token Pruning For Efficient Vision-Language Models

Yvon Apedo, Martyna Poreba, Michal Szczepanski, Samia Bouchafa ยท 2026

Vision-Language Models (VLM) have revolutionized multimodal learning by jointly processing visual and textual information. Yet, they face significant challenges due to the high computational and memorโ€ฆ

Read Paper โ†’
AI & Data Science Preprint PDF DOI

Triviality Corrected Endogenous Reward

Xinda Wang, Zhengxu Hou, Yangshijie Zhang, Bingren Yan, Jialin Liu, Chenzhuo Zhao, Zhibo Yang, Bin-Bin Yang, Feng Xiao ยท 2026

Reinforcement learning for open-ended text generation is constrained by the lack of verifiable rewards, necessitating reliance on judge models that require either annotated data or powerful closed-souโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Gia-Wei Chern, Yunhao Fan, Sheng Zhang, Puhan Zhang ยท 2026

We review recent advances in machine-learning (ML) force-field methods for large-scale Landau-Lifshitz-Gilbert (LLG) simulations of metallic spin systems. We generalize the Behler-Parrinello (BP) ML aโ€ฆ

Read Paper โ†’
โ† Prev Page 143 of 17334 Next โ†’