arXiv:2609.37356v1 Announce Type: new
Abstract: Generating optimization instances that are both feasible and computationally challenging is crucial for benchmarking solvers and training learning-base...
By Jitin Singla, Parikshit Pareek, Pratik Jawanpuria, Parag Singla
arXiv:2609.37454v1 Announce Type: new
Abstract: Underwriters in commercial Property and Casualty (P&C) insurance spend 30 to 40% of their time on administrative work rather than risk judgment, and a...
By Vivek Kumar Singh, Gautam Bhowmick
arXiv:2609.37544v1 Announce Type: new
Abstract: Content-generation agents continuously receive impressions, clicks, conversions, and negative feedback from recommendation systems, providing real-worl...
By Shanwen Mao, Mingming Li, Hao Zhang, Zhiheng Li, Yige Wang, Penghua Yu, Junxiong Zhu
arXiv:2609.37658v1 Announce Type: new
Abstract: LLM agents are increasingly expected to support enterprise workflows, where tasks often involve missing information, uncertainty, feedback, and long-te...
By Min Yang, Yichen Pan, Jinghua Piao, Dandan Song, Yongshun Gong, Yong Li
arXiv:2609.37950v1 Announce Type: new
Abstract: Video understanding agents acquire evidence through an executable harness that controls what they observe and how they use those observations. However,...
By Bingjun Luo, Jialin Guo, Siqi Li
arXiv:2609.38043v1 Announce Type: new
Abstract: Interactive agent benchmarks and multi-turn reinforcement learning increasingly place a second language model in the role of the user. This simulated u...
By Ashish Jain, Armaan Sandhu
arXiv:2609.38108v1 Announce Type: new
Abstract: Large language models (LLMs) enable agents to solve long-horizon tasks by generating a plan and then executing it in an environment. However, successfu...
By Subba Reddy Oota, Francisco Herrera, Jordi Cabot Sagrera, Marcos L\'opez de Prado, Shadab Khan
arXiv:2609.35814v1 Announce Type: cross
Abstract: As browser-use agents improve, benchmarks keep pace by collecting new tasks, websites, and applications, often making tasks longer or more novel. Thi...
By Xunjian Yin, Tianchen Guan, Jinao Wang, Weili Cao, Daisy Xinlei Lin, Royce Cheng-Yue, Keagan Long, Kyle Wong, Bhuwan Dhingra, Xiangjun Wang, Shuyan Zhou
arXiv:2609.35811v1 Announce Type: cross
Abstract: Tool retrieval is a critical bottleneck for LLM-based agents operating over large, heterogeneous API ecosystems. Existing approaches face an inherent...
By Zongze Wu, Yani Guo, Runnan Li
arXiv:2609.35816v1 Announce Type: cross
Abstract: Large language model search agents are often trained with synthetic questions whose difficulty is increased through larger evidence graphs, additiona...
By Linzhi Peng, Hanting Chen, Heng Chang, Ke Cheng, Bowen Du, Weifeng Lv
arXiv:2609.35839v1 Announce Type: cross
Abstract: Handclaps provide an equipment-free excitation for room acoustics, but their unknown and variable source waveform makes room impulse response (RIR) e...
By Shih-Yu Lai, Kyung Yun Lee, Nils Meyer-Kahlen, Eloi Moliner, Bing-Yu Chen, Vesa V\"alim\"aki
arXiv:2609.35841v1 Announce Type: cross
Abstract: Mutation testing evaluates test-suite adequacy by injecting synthetic faults into program code. However, traditional rule-based tools often generate...
By Nils Kiele, Zainab Saad, Zirui Wang, Steve Drew, Samira Ebrahimi Kahou
arXiv:2609.35879v1 Announce Type: cross
Abstract: Benchmarks for large language models (LLMs) typically evaluate the accuracy of answers against fixed reference labels. But a central step in many com...
By Hui Dai, Lina Piao, Nick Merrill, Nadja Flechner, Ezra Karger, Haifeng Xu
arXiv:2609.35928v1 Announce Type: cross
Abstract: Multi-agent LLM systems increasingly mix models from several providers, yet exposing each agent's underlying model identity to its peers significantl...
By Xavier Del Giudice, Alessio Palma, Matteo Migliarini, Fabio Galasso, Indro Spinelli
arXiv:2609.35952v1 Announce Type: cross
Abstract: We introduce HEAR (Human-recorded Evaluation of Audio-LLM bias by Real speakers), a large-scale, ecologically valid benchmark comprising 87k real hum...
By Shen Yan, Duc Le, Irina-Elena Veliche
arXiv:2609.35965v1 Announce Type: cross
Abstract: Vision-and-Language Navigation (VLN) has largely focused on a single agent following a single instruction, yet many real-world applications require t...
By Yunzhe Xu, Zhe Liu
arXiv:2609.36087v1 Announce Type: cross
Abstract: Clinicians and neuroscientists have long analyzed intracranial electroencephalography (iEEG) through directly measurable physiological characteristic...
By Yipeng Zhang, Chenda Duan, Yuanyi Ding, Tianyi Wang, Atsuro Daida, Masaki Izumi, Yuta Tanoue, Naoto Kuroda, Shaun A. Hussain, Nishant Sinha, Eishi Asano. Hiroki Nariai, Vwani Roychowdhury
arXiv:2609.36167v1 Announce Type: cross
Abstract: Distributed Denial of Service attacks are a growing threat to network infrastructure, and new techniques, including the use of generative AI, make th...
By Aadith Sukumar, Isha Singh, Devershika Mohane, Ankit Mukherjee, Ankush Dutta, Rahee Walambe, Ketan Kotecha
arXiv:2609.36173v1 Announce Type: cross
Abstract: Parallel speculative drafting generates multiple candidates in one backbone pass, but independent token selection can produce inconsistent continuati...
By Haohui Zhang, Keyu Chen, Haocheng Sun, Weibo Gu, Ruizhi Qiao, Xing Sun, Bo Jiang
arXiv:2609.36201v1 Announce Type: cross
Abstract: Computer-use agents (CUAs), while capable of completing computer tasks in everyday and professional workflows, can cause unintended harm even under b...
By Jianxing Chen, Xiao Yu, Shipra Agrawal, Zhou Yu