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arXiv:2604.02709v1 Announce Type: new Abstract: The formal reasoning capabilities of LLMs are crucial for advancing automated software engineering. However, existing benchmarks for LLMs lack systematic …
arXiv:2604.02637v1 Announce Type: new Abstract: As large language models (LLMs) become increasingly persuasive, there is concern that people's opinions and decisions may be influenced across …
arXiv:2604.02734v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong potential in long-horizon decision-making tasks, such as embodied manipulation and web interaction. However, …
arXiv:2604.02344v1 Announce Type: new Abstract: WebGPU's security-focused design imposes per-operation validation that compounds across the many small dispatches in neural network inference, yet the true …
arXiv:2604.02528v1 Announce Type: new Abstract: The new Specifications for the National Bridge Inventory (SNBI), in effect from 2022, emphasize the use of element-level condition states …
arXiv:2305.18915v1 Announce Type: cross Abstract: In this work we build upon negative results from an attempt at language modeling with predicted semantic structure, in order …
arXiv:2604.02866v1 Announce Type: new Abstract: Knowledge Graph construction from natural language requires extracting structured triplets from complex, information-dense sentences. In this paper, we investigate if …
arXiv:2604.02460v1 Announce Type: new Abstract: Recent work reports strong performance from multi-agent LLM systems (MAS), but these gains are often confounded by increased test-time computation. …
arXiv:2604.02640v1 Announce Type: new Abstract: Performance evaluation of Retrieval-Augmented Generation (RAG) systems within enterprise environments is governed by multi-dimensional and composite factors extending far beyond …
The article examines the legal aspects of regulating artificial intelligence in the context of digital diplomacy. The author examines the process of transformation of traditional …
arXiv:2604.02527v1 Announce Type: new Abstract: The recent advancement of Large Language Models (LLMs) offers new opportunities to generate user preference data to warm-start bandits. Recent …
arXiv:2604.02633v1 Announce Type: new Abstract: Non-Exemplar Continual Graph Learning (NECGL) seeks to eliminate the privacy risks intrinsic to rehearsal-based paradigms by retaining solely class-level prototype …