Papers
Research papers from arXiv and related sources
Initial Performance of a Long Axial FOV PET with TOF and DOI capabilities: IMAS system
This work summarizes the design, construction, initial performance evaluation and pilot clinical results of the IMAS system, a long axial field of view (FOV), also known as total-body (TB-), positr...
Antonio J. Gonzalez, Alvaro Anreus-Valero, David Sanchez, Santiago Jiménez-Serrano, Marta Freire,...
Stepping VLMs onto the Court: Benchmarking Spatial Intelligence in Sports
Sports have long attracted broad attention as they push the limits of human physical and cognitive capabilities. Amid growing interest in spatial intelligence for vision-language models (VLMs), spo...
Yuchen Yang, Yuqing Shao, Duxiu Huang, Linfeng Dong, Yifei Liu, Suixin Tang, Xiang Zhou, Yuanyuan...
A Survey on Cloud-Based 6G Deployments: Current Solutions, Future Directions and Open Challenges
The next generation of cellular networks is designed to provide ubiquitous connectivity to a wide range of devices. As Telecommunication Service Providers (TSPs) increasingly collaborate with publi...
Tolga O. Atalay, Alireza Famili, Amirreza Ghafoori, Angelos Stavrou
MSSR: Memory-Aware Adaptive Replay for Continual LLM Fine-Tuning
Continual fine-tuning of large language models (LLMs) is becoming increasingly crucial as these models are deployed in dynamic environments where tasks and data distributions evolve over time. Whil...
Yiyang Lu, Yu He, Jianlong Chen, Hongyuan Zha
Overview of the TREC 2025 Retrieval Augmented Generation (RAG) Track
The second edition of the TREC Retrieval Augmented Generation (RAG) Track advances research on systems that integrate retrieval and generation to address complex, real-world information needs. Buil...
Shivani Upadhyay, Nandan Thakur, Ronak Pradeep, Nick Craswell, Daniel Campos, Jimmy Lin
Influencing LLM Multi-Agent Dialogue via Policy-Parameterized Prompts
Large Language Models (LLMs) have emerged as a new paradigm for multi-agent systems. However, existing research on the behaviour of LLM-based multi-agents relies on ad hoc prompts and lacks a princ...
Hongbo Bo, Jingyu Hu, Weiru Liu
Optimal Universal Bounds for Quantum Divergences
We identify a universal structural principle underlying the smoothing of classical divergences: the optimizer of the smoothing problem is a clipped probability vector, independently of the specific...
Gilad Gour
Benchmarking Political Persuasion Risks Across Frontier Large Language Models
Concerns persist regarding the capacity of Large Language Models (LLMs) to sway political views. Although prior research has claimed that LLMs are not more persuasive than standard political campai...
Zhongren Chen, Joshua Kalla, Quan Le
DISPLAY: Directable Human-Object Interaction Video Generation via Sparse Motion Guidance and Multi-Task Auxiliary
Human-centric video generation has advanced rapidly, yet existing methods struggle to produce controllable and physically consistent Human-Object Interaction (HOI) videos. Existing works rely on de...
Jiazhi Guan, Quanwei Yang, Luying Huang, Junhao Liang, Borong Liang, Haocheng Feng, Wei He, Kaisi...
Do What I Say: A Spoken Prompt Dataset for Instruction-Following
Speech Large Language Models (SLLMs) have rapidly expanded, supporting a wide range of tasks. These models are typically evaluated using text prompts, which may not reflect real-world scenarios whe...
Maike Züfle, Sara Papi, Fabian Retkowski, Szymon Mazurek, Marek Kasztelnik, Alexander Waibel, Lui...
The role of mass loss in constraining quenching time in dwarf galaxies from AGB and RGB star counts
The capability of reconstructing the past star formation history of dwarf elliptical galaxies out of the Local Volume relies on modelling bright stellar populations currently evolving through t...
Paolo Ventura, Richard D'Souza, Flavia Dell'Agli, Eric Bell, Claudio Gavetti, Chiara Fiumi, Marco...
MissBench: Benchmarking Multimodal Affective Analysis under Imbalanced Missing Modalities
Multimodal affective computing underpins key tasks such as sentiment analysis and emotion recognition. Standard evaluations, however, often assume that textual, acoustic, and visual modalities are ...
Tien Anh Pham, Phuong-Anh Nguyen, Duc-Trong Le, Cam-Van Thi Nguyen
CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning
Accurately quantifying terrestrial carbon exchange is essential for climate policy and carbon accounting, yet models must generalize to ecosystems underrepresented in sparse eddy covariance observa...
Aleksei Rozanov, Arvind Renganathan, Yimeng Zhang, Vipin Kumar
A Graph-Based Approach to Spectrum Demand Prediction Using Hierarchical Attention Networks
The surge in wireless connectivity demand, coupled with the finite nature of spectrum resources, compels the development of efficient spectrum management approaches. Spectrum sharing presents a pro...
Mohamad Alkadamani, Halim Yanikomeroglu, Amir Ghasemi
Polarization transfer in $ψ'\toψππ$: a complete spin density matrix analysis framework
A theoretical framework based on the Spin Density Matrix (SDM) formalism is developed to describe polarization transfer in the decay chain $e^+e^- \rightarrow ψ^\prime \rightarrow ψππ$. Explicit re...
Jiabao Gong, Guanyu Wang, Dongyu Yuan, Libo Liao, Yilun Wang, Jiarong Li, Xiaoshen Kang, Lei Zhan...
Modeling structure and credit risk of the economy: a multilayer bank-firm network approach
Assessing the resilience of the economy requires accounting for its intrinsic multi-layer nature, by assessing for instance how disruptions at the firm level spread through the production network a...
Soumen Majhi, Anna Mancini, Giulio Cimini
SCENEBench: An Audio Understanding Benchmark Grounded in Assistive and Industrial Use Cases
Advances in large language models (LLMs) have enabled significant capabilities in audio processing, resulting in state-of-the-art models now known as Large Audio Language Models (LALMs). However, m...
Laya Iyer, Angelina Wang, Sanmi Koyejo
Materials Acceleration Platform for Electrochemistry (MAP-E): a Platform for Autonomous Electrochemistry
Corrosion testing is slow, labor-intensive, and sensitive to operator technique, limiting the generation of large, high-quality datasets for data-driven materials discovery. We introduce the Materi...
Daniel Persaud, Mike Werezak, Mark Xu, Melyne Zhou, Frank Benkel, Xin Pang, Vahid Attari, Brian D...
RecThinker: An Agentic Framework for Tool-Augmented Reasoning in Recommendation
Large Language Models (LLMs) have revolutionized recommendation agents by providing superior reasoning and flexible decision-making capabilities. However, existing methods mainly follow a passive i...
Haobo Zhang, Yutao Zhu, Kelong Mao, Tianhao Li, Zhicheng Dou
Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
Sequential multi-agent reasoning frameworks such as Chain-of-Agents (CoA) handle long-context queries by decomposing inputs into chunks and processing them sequentially using LLM-based worker agent...
Naman Gupta, Vaibhav Singh, Arun Iyer, Kirankumar Shiragur, Pratham Grover, Ramakrishna B. Bairi,...