Papers
Research papers from arXiv and related sources
Sensing-Assisted Adaptive Beam Probing with Calibrated Multimodal Priors and Uncertainty-Aware Scheduling
Highly directional mmWave/THz links require rapid beam alignment, yet exhaustive codebook sweeps incur prohibitive training overhead. This letter proposes a sensing-assisted adaptive probing policy...
Abidemi Orimogunje, Vukan Ninkovic, Ognjen Kundacina, Hyunwoo Park, Sunwoo Kim, Dejan Vukobratovi...
Schema on the Inside: A Two-Phase Fine-Tuning Method for High-Efficiency Text-to-SQL at Scale
Applying large, proprietary API-based language models to text-to-SQL tasks poses a significant industry challenge: reliance on massive, schema-heavy prompts results in prohibitive per-token API cos...
Chinmay Soni, Shivam Chourasia, Gaurav Kumar, Hitesh Kapoor
Precision Tests of Isospin Symmetry through Coulomb excitation of A = 62 Nuclei
Isospin symmetry in the $A=62$ mass system was investigated through Coulomb excitation reactions at the RIKEN Radioactive Isotope Beam Factory. Beams of $^{62}$Zn, $^{62}$Ga, and $^{62}$Ge were stu...
K. Wimmer, T. Hüyük, S. M. Lenzi, A. Poves, F. Browne, P. Doornenbal, T. Koiwai, T. Arici, M. A. ...
COVTrack++: Learning Open-Vocabulary Multi-Object Tracking from Continuous Videos via a Synergistic Paradigm
Multi-Object Tracking (MOT) has traditionally focused on a few specific categories, restricting its applicability to real-world scenarios involving diverse objects. Open-Vocabulary Multi-Object Tra...
Zekun Qian, Wei Feng, Ruize Han, Junhui Hou
Language-Grounded Multi-Agent Planning for Personalized and Fair Participatory Urban Sensing
Participatory urban sensing leverages human mobility for large-scale urban data collection, yet existing methods typically rely on centralized optimization and assume homogeneous participants, resu...
Xusen Guo, Mingxing Peng, Hongliang Lu, Hai Yang, Jun Ma, Yuxuan Liang
CVPD at QIAS 2026: RAG-Guided LLM Reasoning for Al-Mawarith Share Computation and Heir Allocation
Islamic inheritance (Ilm al-Mawarith) is a multi-stage legal reasoning task requiring the identification of eligible heirs, resolution of blocking rules (hajb), assignment of fixed and residual sha...
Wassim Swaileh, Mohammed-En-Nadhir Zighem, Hichem Telli, Salah Eddine Bekhouche, Abdellah Zakaria...
Analyzing animal movement using deep learning
Understanding how animals move through heterogeneous landscapes is central to ecology and conservation. In this context, step selection functions (SSFs) have emerged as the main statistical framewo...
Thibault Fronville, Maximilian Pichler, Johannes Signer, Marius Grabow, Stephanie Kramer-Schadt, ...
Gravitational mass generation and consistent non-minimal couplings: cubics and quartics of a massive vector
An attempt to evade the strict uniqueness of consistent interactions involving spin-2 particles is made by modifying the Noether procedure from the outset. A vector field is introduced, coupled to ...
Carlo Marzo
UW-VOS: A Large-Scale Dataset for Underwater Video Object Segmentation
Underwater Video Object Segmentation (VOS) is essential for marine exploration, yet open-air methods suffer significant degradation due to color distortion, low contrast, and prevalent camouflage. ...
Hongshen Zhao, Jingkang Tai, Yuhang Wu, Wenkang Zhang, Xi Lan, Shangyan Wang, Tianyu Zhang, Wanko...
Thinking with Tables: Enhancing Multi-Modal Tabular Understanding via Neuro-Symbolic Reasoning
Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across modalities such as images and text. However, tabular data, despite being a critical real-world mo...
Kun-Yang Yu, Zhi Zhou, Shi-Yu Tian, Xiao-Wen Yang, Zi-Yi Jia, Ming Yang, Zi-Jian Cheng, Lan-Zhe G...
Forensic Implications of Localized AI: Artifact Analysis of Ollama, LM Studio, and llama.cpp
The proliferation of local Large Language Model (LLM) runners, such as Ollama, LM Studio and llama.cpp, presents a new challenge for digital forensics investigators. These tools enable users to dep...
Shariq Murtuza
Understanding the Challenges in Iterative Generative Optimization with LLMs
Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using execution feedback. It is a promising approach to building self...
Allen Nie, Xavier Daull, Zhiyi Kuang, Abhinav Akkiraju, Anish Chaudhuri, Max Piasevoli, Ryan Rong...
From Untamed Black Box to Interpretable Pedagogical Orchestration: The Ensemble of Specialized LLMs Architecture for Adaptive Tutoring
Monolithic Large Language Models (LLMs) used in educational dialogue often behave as "black boxes," where pedagogical decisions are implicit and difficult to audit, frequently violating instruction...
Nizam Kadir
CoCR-RAG: Enhancing Retrieval-Augmented Generation in Web Q&A via Concept-oriented Context Reconstruction
Retrieval-augmented generation (RAG) has shown promising results in enhancing Q&A by incorporating information from the web and other external sources. However, the supporting documents retrieved f...
Kaize Shi, Xueyao Sun, Qika Lin, Firoj Alam, Qing Li, Xiaohui Tao, Guandong Xu
Can we generate portable representations for clinical time series data using LLMs?
Deploying clinical ML is slow and brittle: models that work at one hospital often degrade under distribution shifts at the next. In this work, we study a simple question -- can large language model...
Zongliang Ji, Yifei Sun, Andre Amaral, Anna Goldenberg, Rahul G. Krishnan
Diet Your LLM: Dimension-wise Global Pruning of LLMs via Merging Task-specific Importance Score
Large language models (LLMs) have demonstrated remarkable capabilities, but their massive scale poses significant challenges for practical deployment. Structured pruning offers a promising solution...
Jimyung Hong, Jaehyung Kim
SafeFlow: Real-Time Text-Driven Humanoid Whole-Body Control via Physics-Guided Rectified Flow and Selective Safety Gating
Recent advances in real-time interactive text-driven motion generation have enabled humanoids to perform diverse behaviors. However, kinematics-only generators often exhibit physical hallucinations...
Hanbyel Cho, Sang-Hun Kim, Jeonguk Kang, Donghan Koo
BRIDG-Q: Barren-Plateau-Resilient Initialisation with Data-Aware LLM-Generated Quantum Circuits
Quantum circuit initialisation is a key bottleneck in variational quantum algorithms (VQAs), strongly impacting optimisation stability and convergence. Recent work shows that large language models ...
Ngoc Nhi Nguyen, Thai T Vu, John Le, Hoa Khanh Dam, Dung Hoang Duong, Dinh Thai Hoang
SilLang: Improving Gait Recognition with Silhouette Language Encoding
Gait silhouettes, which can be encoded into binary gait codes, are widely adopted to representing motion patterns of pedestrian. Recent approaches commonly leverage visual backbones to encode gait ...
Ruiyi Zhan, Guozhen Peng, Canyu Chen, Jian Lei, Annan Li
Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith
Large language models (LLMs) have achieved remarkable progress in many language tasks, yet they continue to struggle with complex historical and religious Arabic texts such as the Quran and Hadith....
Somaya Eltanbouly, Samer Rashwani