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arXiv:2603.13344v1 Announce Type: new Abstract: The prevailing paradigm in Automated Heuristic Design (AHD) typically relies on the assumption that a single, fixed algorithm can effectively …
arXiv:2603.13691v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel on standardized medical exams, high scores often fail to translate to high-quality responses for …
arXiv:2603.13998v1 Announce Type: new Abstract: While graph-derived signals are widely used in tabular learning, existing studies typically rely on limited experimental setups and average performance …
arXiv:2603.13791v1 Announce Type: new Abstract: Reliable detection of deceptive behavior in Large Language Model (LLM) agents is an essential prerequisite for safe deployment in high-stakes …
arXiv:2603.13230v1 Announce Type: new Abstract: Slang interpretation has been a challenging downstream task for Large Language Models (LLMs) as the expressions are inherently embedded in …
arXiv:2603.13605v1 Announce Type: new Abstract: We introduce Orla, a library for constructing and running LLM-based agentic systems. Modern agentic applications consist of workflows that combine …
arXiv:2603.13245v1 Announce Type: new Abstract: UK planning authorities face a legislative conflict between the Planning Act, which mandates public access to application documents, and the …
arXiv:2603.13356v1 Announce Type: new Abstract: Standard approaches to Robust Reinforcement Learning assume that feedback sources are either globally trustworthy or globally adversarial. In this paper, …
arXiv:2603.13257v1 Announce Type: new Abstract: Deep Reinforcement Learning (DRL) agents achieve remarkable performance in continuous control but remain opaque, hindering deployment in safety-critical domains. Existing …
arXiv:2603.13752v1 Announce Type: new Abstract: Recently, Transformer-based architectures have advanced meteorological prediction. However, this position-centric tokenizer conflicts with the core principle of meteorological systems, where …
arXiv:2603.13243v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) generate text via iterative denoising but consistently underperform on multi-step reasoning. We hypothesize this gap …
arXiv:2603.13796v1 Announce Type: new Abstract: High dialogue engagement is a crucial indicator of an effective conversation. A reliable measure of engagement could help benchmark large …