arXiv:2608. 11241v1 Announce Type: new Abstract: Deploying LLM agents into industrial recommender operations exposes a three-way tension we frame as the autonomy-determinism-efficiency trilemma: general autonomy (interpreting operator intent, generating glue code zero-shot), industrial determinism (schema-conforming feature extraction, non-crashing A/B, zero compliance-path hallucination), and end-to-end efficiency.
By Dongyang Ao, Kaixiang Fang, Shijie Xu
arXiv:2607. 17269v1 Announce Type: new Abstract: Large language models encode world models implicitly in neural weights, which exposes four structural risks in high-precision domains such as medicine and finance: hallucination, frozen knowledge, poor explainability, and poor modifiability.
By Zhanbo Li, Shifeng Wu, Xiangjin Meng, Wenjie Cai
arXiv:2606. 13706v1 Announce Type: cross Abstract: We present HierSVA, an integrated suite that combines a pipeline, dataset, and benchmark for LLM-driven hierarchical hardware formal verification.
By Maohua Nie, Jiang Zhu, Jingqun Zhang, Zhichen Zeng, Jiayi Wang, Sibo Zhang, Jialin Wang, C. -J. Richard Shi
arXiv:2608. 05773v1 Announce Type: new Abstract: A geometry-conditioned, neuro-symbolic closed-loop architecture is proposed for laser powder bed fusion, in which a standards-aligned ontology operates inside the control loop and couples symbolic reasoning with statistical learning to set the targets of a constraint-aware predictive controller.
By Gisuk Hong, Jaebong Cho, Hyunbo Cho
arXiv:2607. 16388v1 Announce Type: cross Abstract: Large-scale AI datacenter platforms comprise thousands of heterogeneous hardware components whose validation requires comprehensive fault injection test plans.
By Mohammed-Khalil Ghali, Saurabh Kulkarni, Prathamesh Kulkarni, Rohan Kulkarni, Sangwon Yoon, Daehan Won
arXiv:2607. 22639v1 Announce Type: new Abstract: Parametric retrieval enables LLMs to retrieve tools implicitly by assigning each API a unique virtual token and training the model to generate it via constrained beam search.
By Sai Shruthi Sistla, Ashutosh Hathidara, Christopher Toukmaji, Mayank Shrivastava, Karthikeyan Asokkumar
arXiv:2604. 16870v2 Announce Type: replace-cross Abstract: AI agents increasingly call external tools (file system, network, APIs) through the Model Context Protocol (MCP).
By Daeyeon Son
arXiv:2606. 00131v1 Announce Type: cross Abstract: Post-link optimizers (PLOs) such as Propeller and BOLT have demonstrated that precise, profile-guided code layout can extract significant performance gains from heavily optimized binaries.
By Chaitanya Mamatha Ananda, Rajiv Gupta, Mircea Trofin, Aiden Grossman, Sriraman Tallam, Xinliang David Li, Amir Yazdanbakhsh
arXiv:2604. 00392v2 Announce Type: replace-cross Abstract: Agents that synthesize their own tools ship a second artifact alongside each answer: a software library that future tasks reuse, compose, and depend on.
By Alibek Kaliyev, Artem Maryanskyy
arXiv:2608. 17646v1 Announce Type: new Abstract: This monograph develops elimination geometry (EG), a typed, native-loss, audit-oriented framework for studying when locally optimal objects can be realized by a shared deployment rule.
By Mian Huang, Xueqin Wang
arXiv:2606. 03755v1 Announce Type: new Abstract: Autonomous science is moving from demonstration to infrastructure.
By Linwu Zhu, Liqiang Gao, Yan Chen, Dan Zhu, Jian Huang
arXiv:2605. 17106v2 Announce Type: replace-cross Abstract: Production LLM deployments increasingly maintain heterogeneous model pools spanning order-of-magnitude cost differences.
By Aashna Garg, Siddharth Singha Roy, Jinu Jang, Federico Brancasi, Shengyu Fu