Tootfinder

💡 Energy-efficient ultracompact laser reduces light loss in all directions
#laser

Energy-efficient ultracompact laser reduces light loss in all directions
An international team of scientists led by Nanyang Technological University, Singapore (NTU Singapore) has developed a new type of ultracompact laser that is more energy efficient and consumes less power.

Oberlandesgericht: Vorsicht bei Werbung mit Superlativen für Software
Ein Software-Anbieter darf nicht damit werben, "das einfachste und effizienteste Lernmanagement-System" zu vertreiben. Ein Konkurrent konnte das durchsetzen.

Measuring DEX Efficiency and The Effect of an Enhanced Routing Method on Both DEX Efficiency and Stakeholders' Benefits
Yu Zhang, Claudio J. Tessone
https://arxiv.org/abs/2508.03217

Measuring DEX Efficiency and The Effect of an Enhanced Routing Method on Both DEX Efficiency and Stakeholders' Benefits
The efficiency of decentralized exchanges (DEXs) and the influence of token routing algorithms on market performance and stakeholder outcomes remain underexplored. This paper introduces the concept of Standardized Total Arbitrage Profit (STAP), computed via convex optimization, as a systematic measure of DEX efficiency. We prove that executing the trade order maximizing STAP and reintegrating the resulting transaction fees eliminates all arbitrage opportunities-both cyclic arbitrage within DEXs…

Efficient Agents: Building Effective Agents While Reducing Cost
Ningning Wang, Xavier Hu, Pai Liu, He Zhu, Yue Hou, Heyuan Huang, Shengyu Zhang, Jian Yang, Jiaheng Liu, Ge Zhang, Changwang Zhang, Jun Wang, Yuchen Eleanor Jiang, Wangchunshu Zhou
https://arxiv.org/abs/2508.02694

Efficient Agents: Building Effective Agents While Reducing Cost
The remarkable capabilities of Large Language Model (LLM)-driven agents have enabled sophisticated systems to tackle complex, multi-step tasks, but their escalating costs threaten scalability and accessibility. This work presents the first systematic study of the efficiency-effectiveness trade-off in modern agent systems, addressing the critical need for cost-effective designs without sacrificing performance. We investigate three key questions: (1) How much complexity do agentic tasks inherentl…

FPG-NAS: FLOPs-Aware Gated Differentiable Neural Architecture Search for Efficient 6DoF Pose Estimation
Nassim Ali Ousalah, Peyman Rostami, Anis Kacem, Enjie Ghorbel, Emmanuel Koumandakis, Djamila Aouada
https://arxiv.org/abs/2508.03618

FPG-NAS: FLOPs-Aware Gated Differentiable Neural Architecture Search for Efficient 6DoF Pose Estimation
We introduce FPG-NAS, a FLOPs-aware Gated Differentiable Neural Architecture Search framework for efficient 6DoF object pose estimation. Estimating 3D rotation and translation from a single image has been widely investigated yet remains computationally demanding, limiting applicability in resource-constrained scenarios. FPG-NAS addresses this by proposing a specialized differentiable NAS approach for 6DoF pose estimation, featuring a task-specific search space and a differentiable gating mechan…

Efficient classical computation of the neural tangent kernel of quantum neural networks
Anderson Melchor Hernandez, Davide Pastorello, Giacomo De Palma
https://arxiv.org/abs/2508.04498

Efficient classical computation of the neural tangent kernel of quantum neural networks
We propose an efficient classical algorithm to estimate the Neural Tangent Kernel (NTK) associated with a broad class of quantum neural networks. These networks consist of arbitrary unitary operators belonging to the Clifford group interleaved with parametric gates given by the time evolution generated by an arbitrary Hamiltonian belonging to the Pauli group. The proposed algorithm leverages a key insight: the average over the distribution of initialization parameters in the NTK definition can …

🦠 Ready for market: Engineered yeast boosts clean, cost-efficient chemical production
#biotech

Ready for market: Engineered yeast boosts clean, cost-efficient chemical production
Building on their success developing a cleaner way to make valuable organic acids, researchers from the Center for Advanced Bioenergy and Bioproducts Innovation (CABBI) have pushed one product closer to commercialization with a major upgrade in yield.

Neutralizing Token Aggregation via Information Augmentation for Efficient Test-Time Adaptation
Yizhe Xiong, Zihan Zhou, Yiwen Liang, Hui Chen, Zijia Lin, Tianxiang Hao, Fan Zhang, Jungong Han, Guiguang Ding
https://arxiv.org/abs/2508.03388

Neutralizing Token Aggregation via Information Augmentation for Efficient Test-Time Adaptation
Test-Time Adaptation (TTA) has emerged as an effective solution for adapting Vision Transformers (ViT) to distribution shifts without additional training data. However, existing TTA methods often incur substantial computational overhead, limiting their applicability in resource-constrained real-world scenarios. To reduce inference cost, plug-and-play token aggregation methods merge redundant tokens in ViTs to reduce total processed tokens. Albeit efficient, it suffers from significant performan…

Efficient detection of spectrally multimode squeezed light through optical parametric amplification
Mahmoud Kalash, Ui-Nyung Han, Young-Sik Ra, Maria V. Chekhova
https://arxiv.org/abs/2508.04502

Efficient detection of spectrally multimode squeezed light through optical parametric amplification
Multimode squeezed light is a key resource for high-dimensional photonic quantum technologies, enabling applications in quantum-enhanced sensing, quantum communication, and quantum computing. Efficient detection of such a multimode squeezed state is essential for unlocking its full potential. Optical parametric amplification (OPA) has recently gained attention as a powerful technique offering loss-tolerant, direct broadband detection, and multimode operation. While OPA has been used to characte…

Diffusion Once and Done: Degradation-Aware LoRA for Efficient All-in-One Image Restoration
Ni Tang, Xiaotong Luo, Zihan Cheng, Liangtai Zhou, Dongxiao Zhang, Yanyun Qu
https://arxiv.org/abs/2508.03373 …

Diffusion Once and Done: Degradation-Aware LoRA for Efficient All-in-One Image Restoration
Diffusion models have revealed powerful potential in all-in-one image restoration (AiOIR), which is talented in generating abundant texture details. The existing AiOIR methods either retrain a diffusion model or fine-tune the pretrained diffusion model with extra conditional guidance. However, they often suffer from high inference costs and limited adaptability to diverse degradation types. In this paper, we propose an efficient AiOIR method, Diffusion Once and Done (DOD), which aims to achieve…