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Panthers search for answers after embarrassing loss to Patriots https://www.espn.com/nfl/story/_/id/46414584/nfl-carolina-panthers-dave-canales-david-tepper-bryce-young-week-4-2025

Rule Encoding and Compliance in Large Language Models: An Information-Theoretic Analysis
Joachim Diederich
https://arxiv.org/abs/2510.05106 https://arxiv.o…

Rule Encoding and Compliance in Large Language Models: An Information-Theoretic Analysis
The design of safety-critical agents based on large language models (LLMs) requires more than simple prompt engineering. This paper presents a comprehensive information-theoretic analysis of how rule encodings in system prompts influence attention mechanisms and compliance behaviour. We demonstrate that rule formats with low syntactic entropy and highly concentrated anchors reduce attention entropy and improve pointer fidelity, but reveal a fundamental trade-off between anchor redundancy and at…

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning
Yongrui Chen, Junhao He, Linbo Fu, Shenyu Zhang, Rihui Jin, Xinbang Dai, Jiaqi Li, Dehai Min, Nan Hu, Yuxin Zhang, Guilin Qi, Yi Huang, Tongtong Wu
https://arxiv.org/abs/2508.17905

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning
Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and knowledge graphs in a unified way. Existing USKR methods rely on task-specific strategies or bespoke representations, which hinder their ability to dismantle barriers between different SKR tasks, thereby constraining their overall performance in cross-task scenarios. In this paper, we introduce \textsc{Pandora}, a novel USKR framework that addresses …