arXiv:2601.06352v3 Announce Type: replace
Abstract: Adapting large language models to individual users remains challenging due to the tension between fine-grained personalization and scalable deploym...
By Yutong Song, Jiang Wu, Weijia Zhang, Chengze Shen, Shaofan Yuan, Weitao Lu, Jian Wang, Yu Wang, Nikil Dutt, Amir M. Rahmani
arXiv:2603.05294v3 Announce Type: replace
Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behavio...
By ELita Lobo, Xu Chen, Jingjing Meng, Nan Xi, Yang Jiao, Chirag Agarwal, Yair Zick, Yan Gao
arXiv:2604.07733v2 Announce Type: replace
Abstract: Evaluating strategic decision-making in LLM-based agents requires generative, competitive, and longitudinal environments, yet few benchmarks provid...
By John Chen, Sihan Cheng, Can Gurkan, Mingyi Lin
arXiv:2604.27927v2 Announce Type: replace
Abstract: We introduce a framework called LAPITHS (Language model Analysis through Paradigm grounded Interpretations of Theses about Human likenesS) and use...
By Matteo Da Pelo, Alessio Donvito, Claudio Frongia, Pietro Salis, Antonio Lieto
arXiv:2605.16638v2 Announce Type: replace
Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this pa...
By Jianpeng Cheng, Xian Wu, Jiangfan Zhang, Wentao Bao, Chaitanya Ahuja, Shlok Kumar Mishra, Xuanming Cui, Hanchao Yu, Yang Gao, Fan Xia, Haixing Dai, Frankie Yuan, Zihao Wang, Xiaobing Chen, Qi Guo, Shaodan Zhai, Aashu Singh, Xiangjun Fan, Jun Xiao
arXiv:2509.26200v2 Announce Type: replace-cross
Abstract: Agentic artificial intelligence is a candidate enabler of Level-4 autonomy in sixth-generation (6G) networks, but agents reasoning over a sha...
By Hatim Chergui, Farhad Rezazadeh, Miguel Catalan Cid, Pouria Sayyad Khodashenas, Daniel Camps Mur, Christos Verikoukis
arXiv:2510.26915v2 Announce Type: replace-cross
Abstract: While heterogeneous teams have typically been designed for well-specified missions with known semantics, generative intelligence, i.e., large...
By Zachary Ravichandran, Fernando Cladera, Ankit Prabhu, Jason Hughes, Carlos Nieto-Granda, Varun Murali, Camillo Taylor, George J. Pappas, Vijay Kumar
arXiv:2512.09443v3 Announce Type: replace-cross
Abstract: We investigate how large language models can be used as research tools in scientific computing while preserving mathematical rigor. We propos...
By Chenyi Li, Zhijian Lai, Dong An, Jiang Hu, Zaiwen Wen
arXiv:2603.02266v2 Announce Type: replace-cross
Abstract: Test-Time Scaling has shown notable efficacy in addressing complex problems through scaling inference compute. However, within Large Audio-La...
By Ruixiang Mao, Xiangnan Ma, Dan Chen, Ziming Zhu, Yuan Ge, Aokai Hao, Haishu Zhao, Yifu Huo, Qing Yang, Kaiyan Chang, Xiaoqian Liu, Chenglong Wang, Qiaozhi He, Tong Xiao, Jingbo Zhu
arXiv:2603.03768v2 Announce Type: replace-cross
Abstract: Full-stack human-robot collaboration (HRC) can become brittle when replacing a planner, partner model, coordination policy, or controller cha...
By Hao Zhang, Yisen Li, Ruize Geng, Yves Tseng, Yaru Niu, Ding Zhao, H. Eric Tseng
arXiv:2605.01392v2 Announce Type: replace-cross
Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across software engineering tasks, including soft...
By Yifei Wang, Ruiyin Li, Peng Liang, Yangxiao Cai, Zengyang Li, Mojtaba Shahin, Arif Ali Khan, Qiong Feng
arXiv:2605.02346v2 Announce Type: replace-cross
Abstract: Operational technology (OT) devices run safety-critical physical processes, yet their security testing remains manual and expert-intensive. A...
By Adel ElZemity, Budi Arief, Shujun Li, George Oikonomou, James Pope
arXiv:2605.11269v2 Announce Type: replace-cross
Abstract: Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast wave...
By Tousif Islam, Digvijay Wadekar, Zihan Zhou
arXiv:2608.28021v2 Announce Type: replace-cross
Abstract: Large language models increasingly author Infrastructure-as-Code (IaC), where one insecure default is provisioned straight into production. P...
By Animesh Shaw
arXiv:2609.12551v2 Announce Type: replace-cross
Abstract: AI is beginning to make substantive contributions to LLM inference optimization. Existing AI optimizations are predominantly profiling-based....
By Ziyue Yang, Yuting Jiang, Lei Qu, Peng Cheng
arXiv:2609.25021v1 Announce Type: new
Abstract: Large Language Models (LLMs) tend to add disclaimers like "I'm just an AI" when asked about something related to themselves. The self-reports from such...
By J\k{e}drzej Maczan
arXiv:2609.25237v1 Announce Type: new
Abstract: Post-training is becoming a service (PTaaS): a customer hands an operator data and a goal, and a forward-deployed engineer (FDE) returns a fine-tuned,...
By Weihang Ding, Junfei Zhan
arXiv:2609.25444v1 Announce Type: new
Abstract: This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide...
By Yunhong Zhang, Changjie Cao, Zhihua Zhang, Bingli Liu, Zongjie Cao, Zongyong Cui, Ying Yang
arXiv:2609.25645v1 Announce Type: new
Abstract: Exhaustively evaluating every candidate LLM configuration on every benchmark item to identify a high-performing one is costly. We formulate configurati...
By Qian Xie, Yueli He, Nairen Cao
arXiv:2609.25655v1 Announce Type: new
Abstract: As large language models (LLMs) scale rapidly, dense full-parameter adaptation becomes increasingly expensive, motivating sparse and modular architectu...
By Zhentao Tan, Chang Liu, Yao Liu, Yue Wu, Jieping Ye