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arXiv:2606.00138v1 Announce Type: new Abstract: Finite element analysis (FEA) is the most important numerical approach for solid mechanics. Challenges of FEA include a steep learning curve for entry-l…
arXiv:2606.00103v1 Announce Type: new Abstract: We introduce a multi-turn interactive framework for reasoning evaluation that treats reasoning as active evidence acquisition and belief updating. Where…
arXiv:2606.00102v1 Announce Type: new Abstract: Over the centuries, probability theory has grown from the calculus of games of chance into a central framework for reasoning under uncertainty. This art…
arXiv:2606.00052v1 Announce Type: new Abstract: As Industry 4.0 accelerates the integration of Cyber-Physical Systems (CPS) in manufacturing, robust anomaly detection has become critical for ensuring …
arXiv:2606.00050v1 Announce Type: new Abstract: We present Grokers, an architecture for building persistent, structured comprehension of typed knowledge graphs through bottom-up inductive traversal of…
arXiv:2606.00045v1 Announce Type: new Abstract: Classical continuous-space neural networks fundamentally struggle to lock into exact mathematical symmetries, such as modular arithmetic and non-commuta…
arXiv:2606.00017v1 Announce Type: new Abstract: Training language model agents for multi-agent strategic interaction presents a core difficulty: the quality of any action may depend on future events t…
arXiv:2606.00009v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely and successfully adopted for solving optimization problems having an expensive-to-evaluate, black-box, and non-conv…
arXiv:2606.00008v1 Announce Type: new Abstract: Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly const…
arXiv:2606.00007v1 Announce Type: new Abstract: As AI agents transition from isolated tools to collaborative participants in shared knowledge ecosystems, governing collective knowledge curation become…
arXiv:2606.00005v1 Announce Type: new Abstract: We present the Consilium Protocol, a Byzantine Fault Tolerance-derived architecture for structured multi-model AI deliberation that treats inter-model d…
arXiv:2606.00002v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) decision engines routinely output nominally optimal plans for high-stakes industrial systems. Yet deployment rar…
arXiv:2606.01166v1 Announce Type: new Abstract: Computer-use agents extend language models from text generation to sustained interaction with files, terminals, browsers, and external tools. This shift…
arXiv:2606.01138v1 Announce Type: new Abstract: Agent-memory frameworks - mem0, Letta/MemGPT, Cognee, Zep/Graphiti, MemoryOS, MemTensor - each ship their own SDK, storage layout, and operational vocab…
arXiv:2606.00962v1 Announce Type: new Abstract: Foundational agent interoperability standards, notably the Agent-to-Agent (A2A) protocol and the Model Context Protocol (MCP), have advanced multi-agent…
arXiv:2606.00925v1 Announce Type: new Abstract: Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supply…
arXiv:2606.00918v1 Announce Type: new Abstract: We present a novel, practical attack on the IPv6 Fragment ID generation algorithm of XNU, which is the kernel used by Apple products such as macOS and i…
arXiv:2606.00904v1 Announce Type: new Abstract: Swarm robotics, particularly drone swarms, are used in various safety-critical tasks. While a lot of attention has been given to improving swarm control…
arXiv:2606.00889v1 Announce Type: new Abstract: Phishing attacks remain a major cybersecurity threat, exploiting deceptive URLs to steal sensitive user information. Traditional blacklist and rule-base…
arXiv:2606.00856v1 Announce Type: new Abstract: The Global CVE initiative (GCVE) proposes a decentralized, open, and extensible model for vulnerability identification, publication, and enrichment. It …
arXiv:2606.00813v1 Announce Type: new Abstract: Safety alignment in LLMs does not improve monotonically across model generations. Studying four generations of Google's Gemma family (7B-31B) with quali…
arXiv:2606.00801v1 Announce Type: new Abstract: Current approaches to LLM adversarial testing suffer from coverage gaps: manual red-teaming does not scale, LLM-as-attacker methods exhibit mode collaps…
arXiv:2606.00669v1 Announce Type: new Abstract: Vulnerability discovery on C/C++ source asks the analyst to choose between heavyweight static analysers, which need a working build before a single quer…
arXiv:2606.00654v1 Announce Type: new Abstract: Current backdoor attacks against LLMs are typically manipulated by the attacker and remain passive. In this paper, we introduce the \textbf{Proactive Av…