“The article's intro provides context by mentioning the CEO's background in tech from the OpenNap era, setting the stage for their work on cutting-edge edge AI technology.”

“Llama-3.2-1B-4bit → 464 tok/s”

“In 5 to 10 years, AI will nurture young professionals, and humans and AI will evolve together.”

“Unsloth now enables 7x longer context lengths (up to 12x) for Reinforcement Learning!”

“This article explains the basic mechanisms of RAG using sample code.”

“Unlike prior single-paradigm approaches, which achieve <75% accuracy on out-of-distribution datasets, our method maintains 86.8% average accuracy across seven diverse test sets...”

“Tolan built a voice-first AI companion with GPT-5.1, combining low-latency responses, real-time context reconstruction, and memory-driven personalities for natural conversations.”

“PC-class small language models (SLMs) improved accuracy by nearly 2x over 2024, dramatically closing the gap with frontier cloud-based large language models (LLMs).”

“OmniNeuro is decoder-agnostic, acting as an essential interpretability layer for any state-of-the-art architecture.”

“I’m now achieving 30x real-time speeds on an i7-12700KF. To put that in perspective: it processes one minute of audio in just 2 seconds.”

“はじめに ※ 本記事はmacOS環境を前提としています（terminal-notifierを使用します）”

“Leveraging the LLM-as-a-judge paradigm, Pat-DEVAL introduces Chain-of-Legal-Thought (CoLT), a legally-constrained reasoning mechanism that enforces sequential patent-law-specific analysis.”

“The router achieved 100% accuracy in distinguishing between coding prompts (e.g., import torch) and literary prompts (e.g., To be or not to be).”

“The paper demonstrates conformal multiplet structure together with the hallmark of emergent spacetime supersymmetry through characteristic relations between fermionic and bosonic operators.”

“FoundationSLAM achieves superior trajectory accuracy and dense reconstruction quality across multiple challenging datasets, while running in real-time at 18 FPS.”

“The paper proposes using the gradient cosine similarity of low-confidence examples to predict data efficiency based on a small number of labeled samples.”

“The paper demonstrates that 'extreme-wave phenomena, often treated as deleterious fluctuations, can be harnessed as structural nonlinearity for scalable, energy-efficient neuromorphic photonic inference.'”

“CPJ significantly improves performance: using GPT-5-mini captions, GPT-5-Nano achieves +22.7 pp in disease classification and +19.5 points in QA score over no-caption baselines.”

“Achieved a classification accuracy of 96.25% on the HCPTask dataset.”

“OFL-SAM2 achieves state-of-the-art performance with limited training data.”

“LMG achieves competitive or leading performance, including bulk loading (up to 8.25x faster), point queries (up to 1.49x faster), range queries (up to 4.02x faster than B+Tree), update (up to 1.5x faster on read-write workloads), stability (up to 82.59x lower coefficient of variation), and space usage (up to 1.38x smaller).”

“Each BPS monopole state is naturally labeled by a weight of the relevant $W$-boson representation of $(H^{\vee})^{s}$.”

“DGGT's biggest breakthrough is that it gets rid of the dependence on scene-by-scene optimization, camera calibration, and short frame windows of traditional solutions.”

“BandiK employs a Multi-Armed Bandit (MAB) framework for each task, where the arms correspond to the performance of candidate auxiliary sets realized as multiple output neural networks over train-test data set splits.”

“PP-ACDC achieves asymptotic (exact) average consensus on any strongly connected digraph under appropriately chosen quantization parameters.”

“Tree-based ensemble methods, including Random Forest and XGBoost, proved inherently robust to this violation, achieving an R-squared of 0.765 and RMSE of 0.731 logP units on the test set.”

“AutoFed consistently achieves superior performance across diverse scenarios.”

“Youtu-LLM sets a new state-of-the-art for sub-2B LLMs...demonstrating that lightweight models can possess strong intrinsic agentic capabilities.”

“Experiments demonstrate that Youtu-Agent achieves state-of-the-art performance on WebWalkerQA (71.47%) and GAIA (72.8%) using open-weight models.”

“The model improves multi-hop reasoning accuracy by 16.8 percent on HotpotQA, 14.3 percent on 2WikiMultihopQA, and 19.2 percent on MeetingBank, while improving consistency by 21.5 percent.”

“The model achieves 25.96 dB PSNR and 0.8375 SSIM on the test set, demonstrating its effectiveness in compressing low-resolution video while maintaining good perceptual quality.”

“WM-SAR consistently outperforms existing deep learning and LLM-based methods.”

“DRL-TH outperforms existing methods in various crowded environments. We also implemented DRL-TH control policy on a real UGV and showed that it performed well in real world scenarios.”

“DATAMASK achieves significant improvements of 3.2% on a 1.5B dense model and 1.9% on a 7B MoE model.”

“The distance-aware approach achieves higher accuracy on coarse grids (max. 60%p accuracy gain) with only a moderate verification overhead (approximately 1.4x), making zone encoding the key lever for efficient zero-knowledge spatial checks.”

“MotivNet achieves competitive performance across datasets without cross-domain training.”

“LightningDiT-XL/1+IG achieves FID=1.34 which achieves a large margin between all of these methods. Combined with CFG, LightningDiT-XL/1+IG achieves the current state-of-the-art FID of 1.19.”

“The paper introduces a suite of performance optimizations, including interleaved pipeline scheduling, attention-aware data scheduling for long-sequence training, hierarchical and overlapped communication for expert parallelism, and DVM-based operator fusion.”

“The paper demonstrates significant performance gains on planning datasets in the Blocksworld domain through intrinsic self-critique, without external source such as a verifier.”

“This demo paper aims to democratize cloud adoption by centralizing the essential information required for researchers to successfully train their first Hugging Face model on AWS SageMaker from scratch.”

“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.”

“NIRNL achieves state-of-the-art performance, exhibiting remarkable robustness, especially under high noise rates.”

“The AHA framework, leveraging counterfactual hard negative mining, constructs a high-quality preference dataset that forces models to distinguish strict acoustic evidence from linguistically plausible fabrications.”

“The Hilbert-VLM model achieves a Dice score of 82.35 percent on the BraTS2021 segmentation benchmark, with a diagnostic classification accuracy (ACC) of 78.85 percent.”

“MeLeMaD outperforms state-of-the-art approaches, achieving accuracies of 98.04% on CIC-AndMal2020 and 99.97% on BODMAS.”

“DUALFloodGNN achieves substantial improvements in predicting multiple hydrologic variables while maintaining high computational efficiency.”

“The multimodal Transformer achieves RMSE = 0.90 mm and R^2 = 0.97 on the test set on the eastern Ireland tile (E32N34).”

“Bridge-TS reaches a new record of imputation accuracy in terms of mean square error and mean absolute error, demonstrating the superiority of improving prior for generative time series imputation.”

“The VBSF architecture achieves an accuracy of more than 98%.”

“OmniAgent achieves state-of-the-art performance, surpassing leading open-source and proprietary models by substantial margins of 10% - 20% accuracy.”