“This article introduces recommended books and websites to study the required pre-requisite knowledge.”

“In modern LLM development, Pre-training, SFT, and RLHF are the "three sacred treasures."”

“元来，LLMの構築にはデータの準備から学習．評価まで様々な工程がありますが，統一的なパイプラインを作るには複数のメーカーの異なるツールや独自実装との混合を検討する必要があります．”

“AEF-based models generally exhibit strong performance on all tasks and are competitive with purpose-built RS-ba”

“この記事では、Amazonレビューのテキストデータを使って レビューがポジティブかネガティブかを分類する二値分類タスクを実装しました。”

“One of the inventors of the transformer (the basis of chatGPT aka Generative Pre-Trained Transformer) says that it is now holding back progress.”

“B-Trans effectively leverage the wisdom of crowds, yielding superior semantic diversity while achieving better task performance compared to deterministic baselines.”

“The article quotes a command line example: `embedding-adapters embed --source sentence-transformers/all-MiniLM-L6-v2 --target openai/text-embedding-3-small --flavor large --text "where are restaurants with a hamburger near me"`”

“Dream2Flow overcomes the embodiment gap and enables zero-shot guidance from pre-trained video models to manipulate objects of diverse categories-including rigid, articulated, deformable, and granular.”

“The proposed system consistently outperformed flat multi-class classifiers and pre-trained self-supervised models.”

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

“CLoRA strikes a better balance between learning performance and parameter efficiency, while requiring the fewest GFLOPs for point cloud analysis, compared with the state-of-the-art methods.”

“USF-MAE achieved the highest performance across all evaluation metrics, with 90.57% accuracy, 91.15% precision, 90.57% recall, and 90.71% F1-score.”

“The paper formulates a unified taxonomy for pre-training paradigms, ranging from single-modality baselines to sophisticated unified frameworks.”

“LVLDrive achieves superior performance compared to vision-only counterparts across scene understanding, metric spatial perception, and reliable driving decision-making.”

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

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

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

“DGC achieves background-tissue separation (mean IoU 0.925) and demonstrates unsupervised disease detection through navigable semantic granularity.”

“The paper introduces Embodied Reasoning Intelligence Quotient (ERIQ), a large-scale embodied reasoning benchmark in robotic manipulation, and FACT, a flow-matching-based action tokenizer.”

“A positive correlation between LAP and forecast accuracy indicates the presence and magnitude of lookahead bias.”

“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.”

“StressRoBERTa achieves 82% F1-score, outperforming the best shared task system (79% F1) by 3 percentage points.”

“AnyMS leverages a bottom-up dual-level attention decoupling mechanism to harmonize the integration of text prompt, subject images, and layout constraints.”

“The method demonstrated in this work opens up a new way to achieve fast, universal, and experiment-calibrated XANES prediction.”

“RobustMask successfully certifies over 20% of candidate documents within the top-10 ranking positions against adversarial perturbations affecting up to 30% of their content.”

“The paper introduces a novel framework that leverages a pre-trained text-guided image-to-image translation model and image retrieval model to efficiently generate synthetic defect images.”

“The paper proposes a novel approach called Enhanced Image Representations (EIR) for generating accurate chest X-ray reports.”

“UniReg exhibits robust cross-domain and multi-modal performance comparable to optimization-based methods.”

“GRPO recovers in-distribution performance but degrades cross-dataset transferability.”

“TabiBERT attains 77.58 on TabiBench, outperforming BERTurk by 1.62 points and establishing state-of-the-art on five of eight categories.”

“LAM3C achieves higher performance than the previous self-supervised methods on indoor semantic and instance segmentation.”

“PLaMo 3 NICT 31B Base is a 31B model pre-trained on English and Japanese datasets, developed by Preferred Networks, Inc. collaborative with National Institute of Information and Communications Technology, NICT.”

“Contrary to the intuition that higher distribution entropy facilitates effective exploration, we find that imposing a precision-oriented prior yields a superior exploration space for RL.”

“The article likely contains technical details about the model's inner workings.”

“Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning on top of the existing LFM2 stack.”

“EgoReAct achieves remarkably higher realism, spatial consistency, and generation efficiency compared with prior methods, while maintaining strict causality during generation.”

“Evaluations on the PolyHope-M 2025 benchmark demonstrate strong performance, achieving F1-scores of 95.2% for Urdu binary classification and 65.2% for Urdu multi-class classification, with similarly competitive results in Spanish, German, and English.”

“CLAdapter achieves state-of-the-art performance across diverse data-limited scientific domains, demonstrating its effectiveness in unleashing the potential of foundation vision models via adaptive transfer.”

“SPECTRE establishes a new state-of-the-art for movement decoding, significantly outperforming both supervised baselines and generic SSL approaches.”

“GLUE improves test accuracy by up to 8.5% over data-size weighting and by up to 9.1% over proxy-metric selection.”

“The paper proposes qGAN-QAOA, a unified quantum-circuit workflow in which a pre-trained quantum generative adversarial network encodes the scenario distribution and QAOA optimizes first-stage decisions by minimizing the full two-stage objective, including expected recourse cost.”

“Bright-4B produces morphology-accurate segmentations of nuclei, mitochondria, and other organelles from brightfield stacks alone--without fluorescence, auxiliary channels, or handcrafted post-processing.”

“The paper finds that human-to-robot transfer emerges once the VLA is pre-trained on sufficient scenes, tasks, and embodiments.”

“GatedBias introduces structure-gated adaptation: profile-specific features combine with graph-derived binary gates to produce interpretable, per-entity biases, requiring only ${\sim}300$ trainable parameters.”

“Self-E is the first from-scratch, any-step text-to-image model, offering a unified framework for efficient and scalable generation.”

“SLIM-Brain establishes new state-of-the-art performance on diverse tasks, while requiring only 4 thousand pre-training sessions and approximately 30% of GPU memory comparing to traditional voxel-level methods.”

“"Through 3-5 efficient interaction rounds, Erkang Diagnosis can accurately understand user symptoms, conduct preliminary analysis, and provide valuable diagnostic suggestions and health guidance."”

“The EfficientNet-B0 + DenseNet121 (Eff+Den) fusion model achieves the best overall mean performance (accuracy: 82.89%) with balanced class-wise F1-scores.”

“DIOR outperforms existing training-free baselines, including CLIP.”