arXiv:2504.02181v2 Announce Type: replace
Abstract: The rapid advancements in large Language models (LLMs) have significantly enhanced their reasoning capabilities, driven by various strategies such as multi-agent collaboration. However, unlike the we…
arXiv:2508.00414v3 Announce Type: replace
Abstract: General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence, enabling complex reasoning, web interaction, coding, and autonomous resear…
arXiv:2510.21652v2 Announce Type: replace
Abstract: AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new directions of inquiry; indeed, …
arXiv:2411.16719v4 Announce Type: replace-cross
Abstract: Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Randomization allows networks to see a virtuall…
arXiv:2508.01575v2 Announce Type: replace
Abstract: Long-term time series forecasting (LTSF) underpins critical applications from energy management to weather prediction, yet achieving reliable multi-step-ahead accuracy remains challenging. Existing L…
arXiv:2604.20595v1 Announce Type: cross
Abstract: We establish a mathematical correspondence between state space models, a state-of-the-art architecture for capturing long-range dependencies in data, and an exactly solvable nonlinear oscillator networ…
arXiv:2604.19859v1 Announce Type: new
Abstract: Edge-scale deep research agents based on small language models are attractive for real-world deployment due to their advantages in cost, latency, and privacy. In this work, we study how to train a strong…
arXiv:2604.19877v1 Announce Type: new
Abstract: We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices — Full Attention (FA), Sliding Window Attention (SWA), Kimi Delta Attention (KDA), and …
arXiv:2604.19903v1 Announce Type: new
Abstract: Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, selective non-catalytic reduction (SNCR), exhibits low…
arXiv:2604.20468v1 Announce Type: cross
Abstract: Industrial robot applications require increasingly flexible systems that non-expert users can easily adapt for varying tasks and environments. However, different adaptations benefit from different inte…