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arXiv:2603.11433v1 Announce Type: new Abstract: In modern transportation networks, adversaries can manipulate routing algorithms using false data injection attacks, such as simulating heavy traffic with …
arXiv:2603.11239v1 Announce Type: new Abstract: The dynamic evolution of real-world necessitates model editing within Large Language Models. While existing methods explore modular isolation or parameter-efficient …
arXiv:2603.11223v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) over Knowledge Graphs (KGs) suffers from the fact that indexing approaches may lose important contextual nuance when …
arXiv:2603.11768v1 Announce Type: new Abstract: Long-term memory has emerged as a foundational component of autonomous Large Language Model (LLM) agents, enabling continuous adaptation, lifelong multimodal …
arXiv:2603.11409v1 Announce Type: new Abstract: Existing voice AI assistants treat every detected pause as an invitation to speak. This works in dyadic dialogue, but in …
arXiv:2603.11067v1 Announce Type: new Abstract: Large language models (LLMs) achieve remarkable performance, yet further gains often require costly training. This has motivated growing interest in …
arXiv:2603.11353v1 Announce Type: new Abstract: Many assumptions that underpin human concepts of identity do not hold for machine minds that can be copied, edited, or …
arXiv:2603.11594v1 Announce Type: new Abstract: Chemotherapy for cancer treatment is costly and accompanied by severe side effects, highlighting the critical need for early prediction of …
arXiv:2603.11455v1 Announce Type: new Abstract: This study examines users' behavioural intention to use OpenClaw through the Cognition--Affect--Conation (CAC) framework. The research investigates how cognitive perceptions …
arXiv:2603.11178v1 Announce Type: new Abstract: Standard LLM distillation wastes compute on two fronts: problems the student has already mastered (near-zero gradients) and problems far beyond …
arXiv:2603.11295v1 Announce Type: new Abstract: Languages change over time. Computational models can be trained to recognize such changes enabling them to estimate the publication date …
arXiv:2603.11382v1 Announce Type: new Abstract: Autonomous agents, especially delegated systems with memory, persistent context, and multi-step planning, pose a measurement problem not present in stateless …