May 2026· arXiv.org· Vol abs/2606.00089· 0 citations· 56 references
Computer Science
TL;DR
This work formalizes this prediction-control interface, separate the scalar trigger from its channel-wise diagnostic log, and establishes that an all-pairs displacement term is redundant within a maximum that already contains the corresponding one-step term.
Abstract
Can learned state-action proposals exist in the physical world? Before executing a proposed action sequence, a robot can inspect empirical variation and disagreement with a learned transition model. However, aggregating these diagnostic signals obscures whether a proposal is inconsistent with the predictor or merely departs from recorded behavior. We formalize this prediction-control interface, separate the scalar trigger from its channel-wise diagnostic log, and establish that an all-pairs displacement term is redundant within a maximum that already contains the corresponding one-step term. We evaluate the monitors on 700 nominal and 5,250 synthetically perturbed 32-transition PushT windows, observing only planar pusher positions and goals. The transition-RMSE baseline achieves a ROC-AUC of 0.982, compared with 0.957 for a heterogeneous maximum and 0.972 for a spread-scaled residual.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
This work revisits schema linking when using the latest generation of large language models (LLMs) and finds empirically that newer models are adept at utilizing relevant schema elements during generation even in the presence of large numbers of irrelevant ones.
Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz et al.· arXiv.org· 109 citations· ⚡19
A novel threat is unveiled in which attackers steer the RAG system's response by injecting malicious passages into its knowledge base, enabling the attacker to steer the response without altering the user input or modifying the RAG weights.
Jiaqi Xue, Meng Zheng, Yebowen Hu et al.· arXiv.org· 109 citations· ⚡8
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