Papers
Research papers from arXiv and related sources
Normative Common Ground Replication (NormCoRe): Replication-by-Translation for Studying Norms in Multi-agent AI
In the late 2010s, the fashion trend NormCore framed sameness as a signal of belonging, illustrating how norms emerge through collective coordination. Today, similar forms of normative coordination...
Luca Deck, Simeon Allmendinger, Lucas Müller, Niklas Kühl
Metadensity functional learning for classical fluids: Regularizing with pair correlations
We investigate and exploit consequences of the recent neural metadensity functional theory [Kampa et al., Phys. Rev. Lett. 134, 107301 (2025), 10.1103/PhysRevLett.134.107301] for describing the phy...
Stefanie M. Kampa, Florian Sammüller, Matthias Schmidt
CHiL(L)Grader: Calibrated Human-in-the-Loop Short-Answer Grading
Scaling educational assessment with large language models requires not just accuracy, but the ability to recognize when predictions are trustworthy. Instruction-tuned models tend to be overconfiden...
Pranav Raikote, Korbinian Randl, Ioanna Miliou, Athanasios Lakes, Panagiotis Papapetrou
PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agents
Digital footprints (records of individuals' interactions with digital systems) are essential for studying behavior, developing personalized applications, and training machine learning models. Howev...
Minjia Wang, Yunfeng Wang, Xiao Ma, Dexin Lv, Qifan Guo, Lynn Zheng, Benliang Wang, Lei Wang, Jia...
Preliminary analysis of RGB-NIR Image Registration techniques for off-road forestry environments
RGB-NIR image registration plays an important role in sensor-fusion, image enhancement and off-road autonomy. In this work, we evaluate both classical and Deep Learning (DL) based image registratio...
Pankaj Deoli, Karthik Ranganath, Karsten Berns
Kraken*: Architecting Generative, Semantic, and Goal-Oriented Network Management for 6G Wireless Systems
Sixth-generation (6G) wireless networks are expected to support autonomous, immersive, and mission-critical services that require not only extreme data rates and ultra-low latency but also adaptive...
Ian F. Akyildiz, Tuğçe Bilen
Exhaustive Circuit Mapping of a Single-Cell Foundation Model Reveals Massive Redundancy, Heavy-Tailed Hub Architecture, and Layer-Dependent Differentiation Control
Mechanistic interpretability of biological foundation models has relied on selective feature sampling, pairwise interaction testing, and observational trajectory analysis. Each of these can introdu...
Ihor Kendiukhov
Prototype-Based Knowledge Guidance for Fine-Grained Structured Radiology Reporting
Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must make many fine-grained, discrete decisions about rare f...
Chantal Pellegrini, Adrian Delchev, Ege Özsoy, Nassir Navab, Matthias Keicher
MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?
Large language models (LLMs) have demonstrated remarkable capabilities in code generation, yet their potential for generating kernels specifically for mobile de- vices remains largely unexplored. I...
Xingze Zou, Jing Wang, Yuhua Zheng, Xueyi Chen, Haolei Bai, Lingcheng Kong, Syed A. R. Abu-Bakar,...
CogSearch: A Cognitive-Aligned Multi-Agent Framework for Proactive Decision Support in E-Commerce Search
Modern e-commerce search engines, largely rooted in passive retrieval-and-ranking models, frequently fail to support complex decision-making, leaving users overwhelmed by cognitive friction. In thi...
Zhouwei Zhai, Mengxiang Chen, Haoyun Xia, Jin Li, Renquan Zhou, Min Yang
Chem4DLLM: 4D Multimodal LLMs for Chemical Dynamics Understanding
Existing chemical understanding tasks primarily rely on static molecular representations, limiting their ability to model inherently dynamic phenomena such as bond breaking or conformational change...
Xinyu Li, Zhen Zhang, Qi Chen, Anton van den Hengel, Lina Yao, Javen Qinfeng Shi
CoMMET: To What Extent Can LLMs Perform Theory of Mind Tasks?
Theory of Mind (ToM)-the ability to reason about the mental states of oneself and others-is a cornerstone of human social intelligence. As Large Language Models (LLMs) become ubiquitous in real-wor...
Ruirui Chen, Weifeng Jiang, Chengwei Qin, Cheston Tan
Understanding LLM Behavior When Encountering User-Supplied Harmful Content in Harmless Tasks
Large Language Models (LLMs) are increasingly trained to align with human values, primarily focusing on task level, i.e., refusing to execute directly harmful tasks. However, a subtle yet crucial c...
Junjie Chu, Yiting Qu, Ye Leng, Michael Backes, Yun Shen, Savvas Zannettou, Yang Zhang
FlexRec: Adapting LLM-based Recommenders for Flexible Needs via Reinforcement Learning
Modern recommender systems must adapt to dynamic, need-specific objectives for diverse recommendation scenarios, yet most traditional recommenders are optimized for a single static target and strug...
Yijun Pan, Weikang Qiu, Qiyao Ma, Mingxuan Ju, Tong Zhao, Neil Shah, Rex Ying
Accurate prediction of K-edge excitation energies using state-specific self-consistent perturbation theory
We present the application of the recently developed one-body Møller--Plesset perturbation theory (OBMP2) to the prediction of K-edge excited states. OBMP2 is a self-consistent perturbation theory ...
Lan Nguyen Tran
QUARE: Multi-Agent Negotiation for Balancing Quality Attributes in Requirements Engineering
Requirements engineering (RE) is critical to software success, yet automating it remains challenging because multiple, often conflicting quality attributes must be balanced while preserving stakeho...
Haowei Cheng, Milhan Kim, Foutse Khomh, Teeradaj Racharak, Nobukazu Yoshioka, Naoyasu Ubayashi, H...
Silent Speech Interfaces in the Era of Large Language Models: A Comprehensive Taxonomy and Systematic Review
Human-computer interaction has traditionally relied on the acoustic channel, a dependency that introduces systemic vulnerabilities to environmental noise, privacy constraints, and physiological spe...
Kele Xu, Yifan Wang, Ming Feng, Qisheng Xu, Wuyang Chen, Yutao Dou, Cheng Yang, Huaimin Wang
AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization
The integration of dynamic, sparse structures like Mixture-of-Experts (MoE) with parameter-efficient adapters (e.g., LoRA) is a powerful technique for enhancing Large Language Models (LLMs). Howeve...
Qiyang Li, Rui Kong, Yuchen Li, Hengyi Cai, Shuaiqiang Wang, Linghe Kong, Guihai Chen, Dawei Yin
ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics
Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI systems lack direct access to transcriptomic representati...
Omar Coser
Towards heterogeneous parallelism for SPHinXsys
This paper presents a Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method solving the two-equation Reynolds-Averaged Navier-Stokes (RANS) model {for the turbulent wall-bounded flows ...
Xiangyu Hu, Alberto Guarnieri