Papers
Research papers from arXiv and related sources
SpinGQE: A Generative Quantum Eigensolver for Spin Hamiltonians
The ground state search problem is central to quantum computing, with applications spanning quantum chemistry, condensed matter physics, and optimization. The Variational Quantum Eigensolver (VQE) ...
Alexander Holden, Moinul Hossain Rahat, Nii Osae Osae Dade
The Specification Gap: Coordination Failure Under Partial Knowledge in Code Agents
When multiple LLM-based code agents independently implement parts of the same class, they must agree on shared internal representations, even when the specification leaves those choices implicit. W...
Camilo Chacón Sartori
Language-Assisted Image Clustering Guided by Discriminative Relational Signals and Adaptive Semantic Centers
Language-Assisted Image Clustering (LAIC) augments the input images with additional texts with the help of vision-language models (VLMs) to promote clustering performance. Despite recent progress, ...
Jun Ma, Xu Zhang, Zhengxing Jiao, Yaxin Hou, Hui Liu, Junhui Hou, Yuheng Jia
Cross Section Measurements of $\bar{n}p \rightarrow K^{+}K^{-}π^{+}(π^{0})$ via Antineutrons Produced by $J/ψ\to p π^{-} \bar{n}$ Decays
Based on a novel method for producing antineutrons via $J/ψ$ decays, we report a study of $\bar{n}p$ inelastic scattering into final states containing kaons. The analysis uses $(10087\pm44)\times 1...
BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Alibert...
Optimizing Multilingual LLMs via Federated Learning: A Study of Client Language Composition
Federated Learning (FL) of Large Language Models (LLMs) in multilingual environments presents significant challenges stemming from heterogeneous language distributions across clients and disparitie...
Aleix Sant, Jordi Luque, Carlos Escolano
DVM: Real-Time Kernel Generation for Dynamic AI Models
Dynamism is common in AI computation, e.g., the dynamic tensor shapes and the dynamic control flows in models. Due to the long compilation time, existing runtime compilation damages the model effic...
Jingzhi Fang, Xiong Gao, Renwei Zhang, Zichun Ye, Lei Chen, Jie Zhao, Chengnuo Huang, Hui Xu, Xue...
UniScale: Synergistic Entire Space Data and Model Scaling for Search Ranking
Recent advances in Large Language Models (LLMs) have inspired a surge of scaling law research in industrial search, advertising, and recommendation systems. However, existing approaches focus mainl...
Liren Yu, Caiyuan Li, Feiyi Dong, Tao Zhang, Zhixuan Zhang, Dan Ou, Haihong Tang, Bo Zheng
RVLM: Recursive Vision-Language Models with Adaptive Depth
Medical AI systems face two fundamental limitations. First, conventional vision-language models (VLMs) perform single-pass inference, yielding black-box predictions that cannot be audited or explai...
Nicanor Mayumu, Zeenath Khan, Melodena Stephens, Patrick Mukala, Farhad Oroumchian
Environment-Grounded Multi-Agent Workflow for Autonomous Penetration Testing
The increasing complexity and interconnectivity of digital infrastructures make scalable and reliable security assessment methods essential. Robotic systems represent a particularly important class...
Michael Somma, Markus Großpointner, Paul Zabalegui, Eppu Heilimo, Branka Stojanović
Who Benefits from RAG? The Role of Exposure, Utility and Attribution Bias
Large Language Models (LLMs) enhanced with Retrieval-Augmented Generation (RAG) have achieved substantial improvements in accuracy by grounding their responses in external documents that are releva...
Mahdi Dehghan, Graham McDonald
Where Do Your Citations Come From? Citation-Constellation: A Free, Open-Source, No-Code, and Auditable Tool for Citation Network Decomposition with Complementary BARON and HEROCON Scores
Standard citation metrics treat all citations as equal, obscuring the social and structural pathways through which scholarly influence propagates. I introduce Citation-Constellation, a freely avail...
Mahbub Ul Alam
Powerful Teachers Matter: Text-Guided Multi-view Knowledge Distillation with Visual Prior Enhancement
Knowledge distillation transfers knowledge from large teacher models to smaller students for efficient inference. While existing methods primarily focus on distillation strategies, they often overl...
Xin Zhang, Jianyang Xu, Hao Peng, Dongjing Wang, Jingyuan Zheng, Yu Li, Yuyu Yin, Hongbo Wang
SumRank: Aligning Summarization Models for Long-Document Listwise Reranking
Large Language Models (LLMs) have demonstrated superior performance in listwise passage reranking task. However, directly applying them to rank long-form documents introduces both effectiveness and...
Jincheng Feng, Wenhan Liu, Zhicheng Dou
Invisible Threats from Model Context Protocol: Generating Stealthy Injection Payload via Tree-based Adaptive Search
Recent advances in the Model Context Protocol (MCP) have enabled large language models (LLMs) to invoke external tools with unprecedented ease. This creates a new class of powerful and tool augment...
Yulin Shen, Xudong Pan, Geng Hong, Min Yang
The First Generation of AI-Assisted Programming Learners: Gendered Patterns in Critical Thinking and AI Ethics of German Secondary School Students
The first generation of students is learning to program alongside GenAI (Generative Artificial Intelligence) tools, raising questions about how young learners critically engage with them and percei...
Isabella Graßl
Unlocking Few-Shot Capabilities in LVLMs via Prompt Conditioning and Head Selection
Current Large Vision Language Models (LVLMs) excel at many zero-shot tasks like image captioning, visual question answering and OCR. However, these same models suffer from poor performance at image...
Adhemar de Senneville, Xavier Bou, Jérémy Anger, Rafael Grompone, Gabriele Facciolo
Towards Automated Crowdsourced Testing via Personified-LLM
The rapid proliferation and increasing complexity of software demand robust quality assurance, with graphical user interface (GUI) testing playing a pivotal role. Crowdsourced testing has proven ef...
Shengcheng Yu, Yuchen Ling, Chunrong Fang, Zhenyu Chen, Chunyang Chen
Linking Global Science Funding to Research Publications
Funding acknowledgments in scholarly publications provide large-scale trace data on organizations that support scientific research. We present a dataset for linking global science funding organizat...
Jacob Aarup Dalsgaard, Filipi Nascimento Silva, Jin AI
Semantic-Aware Interruption Detection in Spoken Dialogue Systems: Benchmark, Metric, and Model
Achieving natural full-duplex interaction in spoken dialogue systems (SDS) remains a challenge due to the difficulty of accurately detecting user interruptions. Current solutions are polarized betw...
Kangxiang Xia, Bingshen Mu, Xian Shi, Jin Xu, Lei Xie
Sequence-aware Large Language Models for Explainable Recommendation
Large Language Models (LLMs) have shown strong potential in generating natural language explanations for recommender systems. However, existing methods often overlook the sequential dynamics of use...
Gangyi Zhang, Runzhe Teng, Chongming Gao