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arXiv:2603.23507v1 Announce Type: cross Abstract: While Masked Diffusion Language Models (MDLMs) relying on token masking and unmasking have shown promise in language modeling, their computational eff…
arXiv:2603.23506v1 Announce Type: cross Abstract: The rapid proliferation of large language models (LLMs) in healthcare creates an urgent need for scalable and psychometrically sound evaluation method…
arXiv:2509.21545v2 Announce Type: cross Abstract: The possibility of LLM self-awareness and even sentience is gaining increasing public attention and has major safety and policy implications, but the …
arXiv:2504.09604v3 Announce Type: cross Abstract: Many-shot jailbreaking (MSJ) is an adversarial technique that exploits the long context windows of modern LLMs to circumvent model safety training by …
arXiv:2410.02064v3 Announce Type: cross Abstract: It has been reported that LLMs can recognize their own writing. As this has potential implications for AI safety, yet is relatively understudied, we i…
arXiv:2603.24582v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) in organizations is a sequential decision problem constrained by reliability and oversight cost. When deterministic…
arXiv:2603.24572v1 Announce Type: new Abstract: In this article, we focus on search algorithms for two-player perfect information games, whose objective is to determine the best possible strategy, and…
arXiv:2603.24527v1 Announce Type: new Abstract: We introduce incongruent normal form (INF), a structural representation for self-referential semantic sentences. An INF replaces a self-referential sent…
arXiv:2603.24481v1 Announce Type: new Abstract: Miscalibrated confidence scores are a practical obstacle to deploying AI in clinical settings. A model that is always overconfident offers no useful sig…
arXiv:2603.24402v1 Announce Type: new Abstract: Existing automated research systems operate as stateless, linear pipelines, generating outputs without maintaining a persistent understanding of the res…
arXiv:2603.24084v1 Announce Type: new Abstract: Empirical evaluation in multi-objective search (MOS) has historically suffered from fragmentation, relying on heterogeneous problem instances with incom…
arXiv:2603.24065v1 Announce Type: new Abstract: Current prompting paradigms for large language models (LLMs), including Chain-of-Thought (CoT) and Tree-of-Thoughts (ToT), follow linear or tree-structu…
arXiv:2603.24018v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown remarkable general capabilities, yet embodied agents built on them fail at complex tasks, often skipping critic…
arXiv:2603.24014v1 Announce Type: new Abstract: Participatory urban sensing leverages human mobility for large-scale urban data collection, yet existing methods typically rely on centralized optimizat…
arXiv:2603.23964v1 Announce Type: new Abstract: The remarkable progress of reinforcement learning (RL) is intrinsically tied to the environments used to train and evaluate artificial agents. Moving be…
arXiv:2603.23910v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) suggest strong potential for automating analog circuit design. Yet most LLM-based approaches rely on a s…
arXiv:2603.23909v1 Announce Type: new Abstract: While Large Language Models (LLMs) provide semantic flexibility for robotic task planning, their susceptibility to hallucination and logical inconsisten…
arXiv:2603.23873v1 Announce Type: new Abstract: DeepXube is a free and open-source Python package and command-line tool that seeks to automate the solution of pathfinding problems by using machine lea…
arXiv:2603.23857v1 Announce Type: new Abstract: The adoption of generative AI across commercial and legal professions offers dramatic efficiency gains -- yet for law in particular, it introduces a per…
arXiv:2603.23853v1 Announce Type: new Abstract: Combining multiple Vision-Language Models (VLMs) can enhance multimodal reasoning and robustness, but aggregating heterogeneous models' outputs amplifie…
arXiv:2603.23840v1 Announce Type: new Abstract: With the growing demand for intelligent in-vehicle experiences, vehicle-based agents are evolving from simple assistants to long-term companions. This e…
arXiv:2603.23838v1 Announce Type: new Abstract: Lifelong Multi-Agent Path Finding (MAPF) is critical for modern warehouse automation, which requires multiple robots to continuously navigate conflict-f…
arXiv:2603.23749v1 Announce Type: new Abstract: Evaluating AI agents on comprehensive benchmarks is expensive because each evaluation requires interactive rollouts with tool use and multi-step reasoni…
arXiv:2603.23714v1 Announce Type: new Abstract: Large language models have recently been proposed as tools for automated essay scoring, but their agreement with human grading remains unclear. In this …