arXiv:2508.13157v1 Announce Type: cross Abstract: Large Language Model (LLM) exhibits great potential in designing of analog integrated circuits (IC) because…
arXiv:2508.01139v2 Announce Type: replace-cross Abstract: Dataset condensation always faces a constitutive trade-off: balancing performance and fidelity under extreme compression. Existing…
arXiv:2508.12800v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit remarkable problem-solving abilities, but struggle with complex tasks due to…
arXiv:2508.13774v1 Announce Type: cross Abstract: This paper reports on the implementation and evaluation of a Model Context Protocol (MCP) server…
arXiv:2508.13773v1 Announce Type: cross Abstract: Long-term time series forecasting (LTSF) is a fundamental task with wide-ranging applications. Although Transformer-based models…
arXiv:2508.11033v2 Announce Type: replace-cross Abstract: Ho et. al (2024) attempts to estimate the degree of algorithmic progress from language models.…
arXiv:2508.12604v1 Announce Type: cross Abstract: Test-time scaling has proven effective in further enhancing the performance of pretrained Large Language Models…
arXiv:2508.12610v1 Announce Type: cross Abstract: Optical motion capture is a foundational technology driving advancements in cutting-edge fields such as virtual…
arXiv:2508.11584v2 Announce Type: replace-cross Abstract: Deploying multiple machine learning models on resource-constrained robotic platforms for different perception tasks often results…
arXiv:2508.11836v1 Announce Type: new Abstract: World models are defined as a compressed spatial and temporal learned representation of an environment.…
