“The author's personal experience with cigarettes is used to illustrate the point: acknowledging both the negative health impacts and the personal benefits of smoking, and advocating for a realistic assessment of AI's impact.”

“FineTec achieves top-1 accuracies of 89.1% and 78.1% on the challenging Gym99-severe and Gym288-severe settings, respectively, demonstrating its robustness and generalizability.”

“The method achieves approximately $4\sim10 imes$ and $2 imes$ speedups while using $1000$ cores, respectively, under the same level of structural and thermodynamic accuracy and with a reduced memory usage.”

“The exttt{Mgformer}-based module is superior in performance and flexibility. Its representative recall and precision values are 0.79 and 0.76, respectively, and can be modified by adjusting the threshold.”

“The proposed HOOA achieves significant improvements, which reduces average task completion delay by 2.5% and average energy consumption by 3.1% compared with the best-performing benchmark approach and state-of-the-art DRL algorithm, respectively.”

“The calculations indicate that: (i) The $1P$-wave $λ$-mode $Ξ_b$ states $Ξ_b|J^P=1/2^-,1 angle_λ$ and $Ξ_b|J^P=3/2^-,1 angle_λ$ are highly promising candidates for the observed state $Ξ_b(6087)$ and $Ξ_b(6095)/Ξ_b(6100)$, respectively.”

“The paper develops the first algorithm that achieves exact convergence using only time-varying row-stochastic matrices.”

“DyStream could generate video within 34 ms per frame, guaranteeing the entire system latency remains under 100 ms. Besides, it achieves state-of-the-art lip-sync quality, with offline and online LipSync Confidence scores of 8.13 and 7.61 on HDTF, respectively.”

“The paper highlights that the targeted Reasoning RL and Agentic RL stages yield significant gains in their respective capabilities.”

“In cases V and VI, the Hamiltonian analysis yields 8 degrees of freedom, while only 6 and 5 modes are visible at linear order in perturbations, respectively. This indicates that additional modes are strongly coupled on cosmological backgrounds.”

“The proposed model achieves 95.5% and 98.5% accuracy for 4-class and 2-class imbalanced classification problems, respectively.”

“TPI-AI outperforms standalone LightGBM and Bi-LSTM baselines, achieving macro-F1 of 0.9562, 0.9124, 0.8345 on highD and 0.9247, 0.8197, 0.7605 on exiD at T = 1, 2, 3 s, respectively.”

“HyperGRL delivers superior representation quality and generalization across diverse graph structures, achieving average improvements of 1.49%, 0.86%, and 0.74% over the strongest existing methods, respectively.”

“The paper establishes $ ilde{O}(\varepsilon^{-2})$ and $O(\varepsilon^{-2})$ sample complexities for achieving average-time and last-iterate $\varepsilon$-optimality, respectively.”

“GCA-ResUNet achieves Dice scores of 86.11% and 92.64% on Synapse and ACDC benchmarks, respectively, outperforming a range of representative CNN and Transformer-based methods.”

“The method achieved superior performance compared to state-of-the-art methods on BraTS2020, with average Dice scores of 87.55, 79.36, and 62.67 for WT, TC, and ET, respectively, across fifteen missing modality combinations.”

“The paper argues that the distribution of stock returns can be effectively split in two -- for gains and losses -- assuming difference in parameters of their respective stochastic volatilities.”

“The accuracy rate, F1 score, recall rate and AUC of PFed-Signal are 0.887, 0.890, 0.913 and 0.957 respectively, which are higher than the baselines.”

“LLM-PeerReview is conceptually simple and empirically powerful. The two variants of the proposed approach obtain strong results across four datasets, including outperforming the recent advanced model Smoothie-Global by 6.9% and 7.3% points, respectively.”

“FedOLF achieves at least 0.3%, 6.4%, 5.81%, 4.4%, 6.27% and 1.29% higher accuracy than existing works respectively on EMNIST (with CNN), CIFAR-10 (with AlexNet), CIFAR-100 (with ResNet20 and ResNet44), and CINIC-10 (with ResNet20 and ResNet44), along with higher energy efficiency and lower memory footprint.”

“The article mentions the use of pdfplumber, tesseract, and Gemini 3 Flash for PDF processing and Markdown conversion.”

“Different energy systems and development paths will have a decisive impact on the AI development of China and the United States.”

“DA360 shows substantial gains over its base model, achieving over 50% and 10% relative depth error reduction on indoor and outdoor benchmarks, respectively. Furthermore, DA360 significantly outperforms robust panoramic depth estimation methods, achieving about 30% relative error improvement compared to PanDA across all three test datasets.”

“OptiNIC improves time-to-accuracy (TTA) by 2x and increases throughput by 1.6x for training and inference, respectively.”

“T3LLM achieves state-of-the-art performance over strong LLM-based baselines.”

“The proxy MNT model predicts the reflected field at the feeds and the radiated field with accuracies of 40.3 dB and 37.7 dB, respectively, significantly outperforming a simpler benchmark model.”

“The experimental results indicate that the proposed model achieves mean absolute percentage errors (MAPE) of 3.243% and 2.641% for window lengths 20 and 15, respectively.”

“The SmartSnap paradigm allows training LLM-driven agents in a scalable manner, bringing performance gains up to 26.08% and 16.66% respectively to 8B and 30B models.”

“FUSCO achieves up to 3.84x and 2.01x speedups over NCCL and DeepEP (the state-of-the-art MoE communication library), respectively.”

“DPAR reduces token count by 1.81x and 2.06x on Imagenet 256 and 384 generation resolution respectively, leading to a reduction of up to 40% FLOPs in training costs. Further, our method exhibits faster convergence and improves FID by up to 27.1% relative to baseline models.”

“ADT-Tree achieves speedups of 3.13x and 3.05x, respectively, on MS-COCO 2017 and PartiPrompts.”

“LIME achieves 1.7x and 3.7x speedups over state-of-the-art baselines under sporadic and bursty request patterns respectively, without compromising model accuracy.”

“Prior-AttUNet achieves excellent performance across three OCT imaging devices (Cirrus, Spectralis, and Topcon), with mean Dice similarity coefficients of 93.93%, 95.18%, and 93.47%, respectively.”

“The proposed method achieves accuracy, recall, and mean average precision of 96.2%, 93.3%, and 96.7%, respectively, in complex multi-pipeline scenarios.”

“The model integrating structured data points had AUROC, AUPRC, and Brier scores of 0.92, 0.53, and 0.19, respectively.”

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“Their goal is to estimate Ex∼p,y∼q[f(x,y)] to within additive error ε for a bounded function f, known to both parties.”

“The study compares Neural Network and Genetic Algorithm approaches for optimization.”

“The article's focus is on the complementary strengths of the Neyman-Rubin and graphical causal frameworks.”

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“N/A (No direct quote in the provided text)”

“The Positional Encoding in LLMs may appear somewhat mysterious the first time we come across the concept, and for good reasons!”

“Foerster champions open-source AI for responsible, decentralised development.”

“Laura Ruis explains her groundbreaking research into how large language models (LLMs) perform reasoning tasks.”

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“We have fine-tuned CodeLlama-34B and CodeLlama-34B-Python on an internal Phind dataset that achieved 67.6% and 69.5% pass@1 on HumanEval, respectively. GPT-4 achieved 67%.”

“IBM and NASA open source largest geospatial AI foundation model on Hugging Face.”

“They discuss the progress they’ve made at their respective locations, how they achieved it, and where they hope to go from there.”

“The article doesn't contain a direct quote.”