Papers
Research papers from arXiv and related sources
Integrating Causal Machine Learning into Clinical Decision Support Systems: Insights from Literature and Practice
Current clinical decision support systems (CDSSs) typically base their predictions on correlation, not causation. In recent years, causal machine learning (ML) has emerged as a promising way to imp...
Domenique Zipperling, Lukas Schmidt, Benedikt Hahn, Niklas Kühl, Steven Kimbrough
AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model
Existing automated research systems operate as stateless, linear pipelines, generating outputs without maintaining a persistent understanding of the research landscape. They process papers sequenti...
Yunbo Long
The enrichment paradox: critical capability thresholds and irreversible dependency in human-AI symbiosis
As artificial intelligence assumes cognitive labor, no quantitative framework predicts when human capability loss becomes catastrophic. We present a two-variable dynamical systems model coupling ca...
Jeongju Park, Musu Kim, Sekyung Han
When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools
High-quality teacher-child interaction (TCI) is fundamental to early childhood development, yet traditional expert-based assessment faces a critical scalability challenge. In large systems like Chi...
Xingming Li, Runke Huang, Yanan Bao, Yuye Jin, Yuru Jiao, Qingyong Hu
Causal Transfer in Medical Image Analysis
Medical imaging models frequently fail when deployed across hospitals, scanners, populations, or imaging protocols due to domain shift, limiting their clinical reliability. While transfer learning ...
Mohammed M. Abdelsamea, Daniel Tweneboah Anyimadu, Tasneem Selim, Saif Alzubi, Lei Zhang, Ahmed K...
MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization
Despite deep learning's success in chemistry, its impact is hindered by a lack of interpretability and an inability to resolve activity cliffs, where minor structural nuances trigger drastic proper...
Xiangsen Chen, Ruilong Wu, Yanyan Lan, Ting Ma, Yang Liu
Towards Reward Modeling for AI Tutors in Math Mistake Remediation
Evaluating the pedagogical quality of AI tutors remains challenging: standard NLG metrics do not determine whether responses identify mistakes, scaffold reasoning, or avoid revealing the answers. F...
Kseniia Petukhova, Ekaterina Kochmar
Improving Lean4 Autoformalization via Cycle Consistency Fine-tuning
Autoformalization - automatically translating natural language mathematical texts into formal proof language such as Lean4 - can help accelerate AI-assisted mathematical research, be it via proof v...
Arsen Shebzukhov
LATS: Large Language Model Assisted Teacher-Student Framework for Multi-Agent Reinforcement Learning in Traffic Signal Control
Adaptive Traffic Signal Control (ATSC) aims to optimize traffic flow and minimize delays by adjusting traffic lights in real time. Recent advances in Multi-agent Reinforcement Learning (MARL) have ...
Yifeng Zhang, Peizhuo Li, Tingguang Zhou, Mingfeng Fan, Guillaume Sartoretti
Gendered Prompting and LLM Code Review: How Gender Cues in the Prompt Shape Code Quality and Evaluation
LLMs are increasingly embedded in programming workflows, from code generation to automated code review. Yet, how gendered communication styles interact with LLM-assisted programming and code review...
Lynn Janzen, Üveys Eroglu, Dorothea Kolossa, Pia Knöferle, Sebastian Möller, Vera Schmitt, Veroni...
Language-Guided Structure-Aware Network for Camouflaged Object Detection
Camouflaged Object Detection (COD) aims to segment objects that are highly integrated with the background in terms of color, texture, and structure, making it a highly challenging task in computer ...
Min Zhang
Evidence of an Emergent "Self" in Continual Robot Learning
A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a "self," and if so how to differentiate the "self" from othe...
Adidev Jhunjhunwala, Judah Goldfeder, Hod Lipson
Enhancing Efficiency and Performance in Deepfake Audio Detection through Neuron-level dropin & Neuroplasticity Mechanisms
Current audio deepfake detection has achieved remarkable performance using diverse deep learning architectures such as ResNet, and has seen further improvements with the introduction of large model...
Yupei Li, Shuaijie Shao, Manuel Milling, Björn Schuller
Generative Artificial Intelligence and the Knowledge Gap: Toward a New Form of Informational Inequality
The knowledge gap hypothesis suggests that the diffusion of information tends to increase rather than reduce social inequalities. Subsequent research on the digital divide has extended this perspec...
Raphael Morisco
On the Quartic Invariant of Odd Degree Binary Forms
We determine the squarefree part of the scalar factor that arises when the quartic invariant of the generic binary form $F$ of odd degree $2n+1$ is expressed as the discriminant of the unique quadr...
Ashvin Swaminathan
GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents
Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. These applications require agents to perceive rapid stat...
Yunzhe Wang, Runhui Xu, Kexin Zheng, Tianyi Zhang, Jayavibhav Niranjan Kogundi, Soham Hans, Volka...
Towards Semantic-based Agent Communication Networks: Vision, Technologies, and Challenges
The International Telecommunication Union (ITU) identifies "Artificial Intelligence (AI) and Communication" as one of six key usage scenarios for 6G. Agentic AI, characterized by its ca-pabilities ...
Ping Zhang, Rui Meng, Xiaodong Xu, Yaheng Wang, Zixuan Huang, Yiming Liu, Ruichen Zhang, Yinqiu L...
Bridging the Dual Nature: How Integrated Explanations Enhance Understanding of Technical Artifacts
Purpose: Understanding a technical artifact requires grasping both its internal structure (Architecture) and its purpose and significance (Relevance), as formalized by Dual Nature Theory. This cont...
Lutz Terfloth, Heike M. Buhl, Vivien Lohmer, Michael Schaffer, Friederike Kern, Carsten Schulte
Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforcement Learning
Designing effective auxiliary rewards for cooperative multi-agent systems remains a precarious task; misaligned incentives risk inducing suboptimal coordination, especially where sparse task feedba...
Dogan Urgun, Gokhan Gungor
A Large-Scale Study of Telegram Bots
Telegram, initially a messaging app, has evolved into a platform where users can interact with various services through programmable applications, bots. Bots provide a wide range of uses, from mode...
Taro Tsuchiya, Haoxiang Yu, Tina Marjanov, Alice Hutchings, Nicolas Christin, Alejandro Cuevas