arXiv:2510.19316v2 Announce Type: replace
Abstract: Large Multimodal Models encode extensive factual knowledge in their pre-trained weights. However, its knowledge remains static and limited, unable to keep pace with real-world developments, which hin…
arXiv:2605.06130v1 Announce Type: new
Abstract: A persistent skill library allows language model agents to reuse successful strategies across tasks. Maintaining such a library requires three coupled capabilities. The agent selects a relevant skill, ut…
arXiv:2605.06407v1 Announce Type: cross
Abstract: Integrating speech understanding and generation is a pivotal step toward building unified speech models. However, the different representations required for these two tasks currently pose significant c…
arXiv:2605.06472v1 Announce Type: new
Abstract: LLM-based workflows compose specialized agents to execute complex tasks, and these agents usually share substantial context, allowing KV-Cache reuse to save computation. Existing approaches either manage…
A LinkedIn feature that allows paid subscribers to view a list of visitors to their profile should be made available to all EU users free of charge to comply with the region’s General Data Protection Regulation (GDPR), a legal co…
arXiv:2605.03882v1 Announce Type: cross
Abstract: Individuals frequently form deep attachments to physical objects (e.g., plush toys) that usually cannot sense or respond to their emotions. While AI companions offer responsiveness and personalization,…
arXiv:2605.04003v1 Announce Type: cross
Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledge. Off-the-shelf large language model (LLM) assista…
arXiv:2506.00886v3 Announce Type: replace
Abstract: As large language models evolve into tool-augmented agents, a central question remains unresolved: when is external tool use actually justified? Existing agent frameworks typically treat tools as ord…
arXiv:2511.02230v4 Announce Type: replace-cross
Abstract: KV cache management is essential for efficient LLM inference. To maximize utilization, existing inference engines evict finished requests’ KV cache if new requests are waiting. This policy brea…
arXiv:2512.16455v3 Announce Type: replace-cross
Abstract: The rapid growth of Artificial Intelligence and Machine Learning in scientific research has highlighted a gap between industry-standard MLOps tools and platforms, and the unique requirements of…