Towards LLM-generated explanations for Component-based Knowledge Graph Question Answering Systems
arXiv:2508.14553v1 Announce Type: cross Abstract: Over time, software systems have reached a level of complexity that makes it difficult for…
Image2Net: Datasets, Benchmark and Hybrid Framework to Convert Analog Circuit Diagrams into Netlists
arXiv:2508.13157v1 Announce Type: cross Abstract: Large Language Model (LLM) exhibits great potential in designing of analog integrated circuits (IC) because…
Dataset Condensation with Color Compensation
arXiv:2508.01139v2 Announce Type: replace-cross Abstract: Dataset condensation always faces a constitutive trade-off: balancing performance and fidelity under extreme compression. Existing…
Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward
arXiv:2508.12800v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit remarkable problem-solving abilities, but struggle with complex tasks due to…
Agentic DraCor and the Art of Docstring Engineering: Evaluating MCP-empowered LLM Usage of the DraCor API
arXiv:2508.13774v1 Announce Type: cross Abstract: This paper reports on the implementation and evaluation of a Model Context Protocol (MCP) server…
PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
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…
Note on Selection Bias in Observational Estimates of Algorithmic Progress
arXiv:2508.11033v2 Announce Type: replace-cross Abstract: Ho et. al (2024) attempts to estimate the degree of algorithmic progress from language models.…
SSPO: Self-traced Step-wise Preference Optimization for Process Supervision and Reasoning Compression
arXiv:2508.12604v1 Announce Type: cross Abstract: Test-time scaling has proven effective in further enhancing the performance of pretrained Large Language Models…
OpenMoCap: Rethinking Optical Motion Capture under Real-world Occlusion
arXiv:2508.12610v1 Announce Type: cross Abstract: Optical motion capture is a foundational technology driving advancements in cutting-edge fields such as virtual…