Papers
Research papers from arXiv and related sources
How Small Can 6G Reason? Scaling Tiny Language Models for AI-Native Networks
Emerging 6G visions, reflected in ongoing standardization efforts within 3GPP, IETF, ETSI, ITU-T, and the O-RAN Alliance, increasingly characterize networks as AI-native systems in which high-level...
Mohamed Amine Ferrag, Abderrahmane Lakas, Merouane Debbah
LongRLVR: Long-Context Reinforcement Learning Requires Verifiable Context Rewards
Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced the reasoning capabilities of Large Language Models (LLMs) by optimizing them against factual outcomes. However, thi...
Guanzheng Chen, Michael Qizhe Shieh, Lidong Bing
Generative AI in Software Testing: Current Trends and Future Directions
This paper investigates current software testing systems and explores how artificial intelligence, specifically Generative AI, can be integrated to enhance these systems. It begins by examining dif...
Tanish Singla, Qusay H. Mahmoud
NextAds: Towards Next-generation Personalized Video Advertising
With the rapid growth of online video consumption, video advertising has become increasingly dominant in the digital advertising landscape. Yet diverse users and viewing contexts makes one-size-fit...
Yiyan Xu, Ruoxuan Xia, Wuqiang Zheng, Fengbin Zhu, Wenjie Wang, Fuli Feng
LLMs as Strategic Actors: Behavioral Alignment, Risk Calibration, and Argumentation Framing in Geopolitical Simulations
Large language models (LLMs) are increasingly proposed as agents in strategic decision environments, yet their behavior in structured geopolitical simulations remains under-researched. We evaluate ...
Veronika Solopova, Viktoria Skorik, Maksym Tereshchenko, Alina Haidun, Ostap Vykhopen
Recursive Models for Long-Horizon Reasoning
Modern language models reason within bounded context, an inherent constraint that poses a fundamental barrier to long-horizon reasoning. We identify recursion as a core principle for overcoming thi...
Chenxiao Yang, Nathan Srebro, Zhiyuan Li
Recursive Think-Answer Process for LLMs and VLMs
Think-Answer reasoners such as DeepSeek-R1 have made notable progress by leveraging interpretable internal reasoning. However, despite the frequent presence of self-reflective cues like "Oops!", th...
Byung-Kwan Lee, Youngchae Chee, Yong Man Ro
OmniRet: Efficient and High-Fidelity Omni Modality Retrieval
Multimodal retrieval is the task of aggregating information from queries across heterogeneous modalities to retrieve desired targets. State-of-the-art multimodal retrieval models can understand com...
Chuong Huynh, Manh Luong, Abhinav Shrivastava
ClinConsensus: A Consensus-Based Benchmark for Evaluating Chinese Medical LLMs across Difficulty Levels
Large language models (LLMs) are increasingly applied to health management, showing promise across disease prevention, clinical decision-making, and long-term care. However, existing medical benchm...
Xiang Zheng, Han Li, Wenjie Luo, Weiqi Zhai, Yiyuan Li, Chuanmiao Yan, Tianyi Tang, Yubo Ma, Kexi...
Adam Converges Without Any Modification On Update Rules
Adam is the default algorithm for training neural networks, including large language models (LLMs). However, \citet{reddi2019convergence} provided an example that Adam diverges, raising concerns fo...
Yushun Zhang, Bingran Li, Congliang Chen, Zhi-Quan Luo, Ruoyu Sun
Learning from Synthetic Data Improves Multi-hop Reasoning
Reinforcement Learning (RL) has been shown to significantly boost reasoning capabilities of large language models (LLMs) in math, coding, and multi-hop reasoning tasks. However, RL fine-tuning requ...
Anmol Kabra, Yilun Yin, Albert Gong, Kamilė Stankevičiūtė, Dongyoung Go, Johann Lee, Katie Z. Luo...
GenDB: The Next Generation of Query Processing -- Synthesized, Not Engineered
Traditional query processing relies on engines that are carefully optimized and engineered by many experts. However, new techniques and user requirements evolve rapidly, and existing systems often ...
Jiale Lao, Immanuel Trummer
MMNavAgent: Multi-Magnification WSI Navigation Agent for Clinically Consistent Whole-Slide Analysis
Recent AI navigation approaches aim to improve Whole-Slide Image (WSI) diagnosis by modeling spatial exploration and selecting diagnostically relevant regions, yet most operate at a single fixed ma...
Zhengyang Xu, Han Li, Jingsong Liu, Linrui Xie, Xun Ma, Xin You, Shihui Zu, Ayako Ito, Xinyu Hao,...
When an AI Judges Your Work: The Hidden Costs of Algorithmic Assessment
We use an online experiment with a real work task to study whether workers change their behavior when they know AI will be used to judge their work instead of humans. We find that individuals produ...
David Almog, Lucas Lippman, Daniel Martin
Trident: Adaptive Scheduling for Heterogeneous Multimodal Data Pipelines
The rapid adoption of large language models and multimodal foundation models has made multimodal data preparation pipelines critical AI infrastructure. These pipelines interleave CPU-heavy preproce...
Ding Pan, Zhuangzhuang Zhou, Long Qian, Binhang Yuan
Cognitive Prosthetic: An AI-Enabled Multimodal System for Episodic Recall in Knowledge Work
Modern knowledge workplaces increasingly strain human episodic memory as individuals navigate fragmented attention, overlapping meetings, and multimodal information streams. Existing workplace tool...
Lawrence Obiuwevwi, Krzysztof J. Rechowicz, Vikas Ashok, Sachin Shetty, Sampath Jayarathna
Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning
When automating plan generation for a real-world sequential decision problem, the goal is often not to replace the human planner, but to facilitate an iterative reasoning and elicitation process, w...
Guilhem Fouilhé, Rebecca Eifler, Antonin Poché, Sylvie Thiébaux, Nicholas Asher
OpenRad: a Curated Repository of Open-access AI models for Radiology
The rapid developments in artificial intelligence (AI) research in radiology have produced numerous models that are scattered across various platforms and sources, limiting discoverability, reprodu...
Konstantinos Vrettos, Galini Papadaki, Emmanouil Brilakis, Matthaios Triantafyllou, Dimitrios Lev...
Beyond Microservices: Testing Web-Scale RCA Methods on GPU-Driven LLM Workloads
Large language model (LLM) services have become an integral part of search, assistance, and decision-making applications. However, unlike traditional web or microservices, the hardware and software...
Dominik Scheinert, Alexander Acker, Thorsten Wittkopp, Soeren Becker, Hamza Yous, Karnakar Reddy,...
Strategic Advice in the Age of Personal AI
Personal AI assistants have changed how people use institutional and professional advice. We study this new strategic setting in which individuals may stochastically consult a personal AI whose rec...
Yueyang Liu, Wichinpong Park Sinchaisri