“Stay tuned for the most important artificial intelligence and machine learning news and articles.”

“I just want to visualize my loss curve without paying w&b unacceptable pricing ($1 per gpu hour is absurd).”

“ELYZA Lab is introducing models that apply the techniques of image generation AI to text.”

“The Wikimedia Foundation says Microsoft, Meta, Amazon, Perplexity, and Mistral joined Wikimedia Enterprise to get “tuned” API access; Google is already a member.”

“"We take feature …" (The article is truncated so no full quote)”

“We introduce the Ministral 3 series, a family of parameter-efficient dense language models designed for compute and memory constrained applications...”

“How do you design an LLM agent that decides for itself what to store in long term memory, what to keep in short term context and what to discard, without hand tuned heuristics or extra controllers?”

“OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education.”

“Transfer learning with fine-tuning substantially outperforms CNNs trained from scratch for pediatric pneumonia detection, showing near-perfect accuracy.”

“"君の言う通りだよ！」「それは素晴らしいアイデアですね！"”

“Nvidia has used its ballooning fortunes to invest in over 100 AI startups.”

“The paper identifies two distinct topological phases: an SPT phase at half filling stabilized by positive parity coupling, and a topological phase at unit filling stabilized by negative coupling.”

“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 multimodal design achieved an 83% boost in 31P B1 efficiency and a 21% boost in 1H B1 efficiency at the coil center compared to same-sized single-tuned references.”

“ConfigTuner demonstrates up to a 1.36x increase in throughput compared to Megatron-LM.”

“The paper's key finding is that using reduced learning rates for proxy model training yields relative performance that strongly correlates with that of fully tuned large-scale LLM pretraining runs.”

“The multilingual fine-tuned mT5 baseline outperforms most other approaches including zero-shot LLM performance for most metrics.”

“The findings show that omnidirectional polarization-independent nonreciprocity can be achieved utilizing multilayer structures with different magnetization directions that do not follow simple vector summation.”

“UniAct achieves a 19% improvement in the success rate of zero-shot tracking of imperfect reference motions.”

“The Pat-SPECTER model performs best, which is the SPECTER2 model fine-tuned on patents.”

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

“DiffThinker significantly outperforms leading closed source models including GPT-5 (+314.2%) and Gemini-3-Flash (+111.6%), as well as the fine-tuned Qwen3-VL-32B baseline (+39.0%), highlighting generative multimodal reasoning as a promising approach for vision-centric reasoning.”

“RL-tuned models maintain more stable behavioral profiles and resist collapse in reasoning skills, whereas SFT models exhibit sharper drift and overfit to surface patterns.”

“CEC-Zero outperforms supervised baselines by 10--13 F$_1$ points and strong LLM fine-tunes by 5--8 points across 9 benchmarks.”

“The experts prefer plans generated by our finetuned Qwen3-30B-A3B model over the initial model for 70% of research goals, and approve 84% of the automatically extracted goal-specific grading rubrics.”

“Biaxial strain acts as a tuning parameter for Fermi surface topology and magnetic correlations.”

“The paper reveals a fine-grained taxonomy of 32 security issues and 24 solutions across four themes: (1) System and Software, (2) External Tools and Ecosystem, (3) Model, and (4) Data. It also highlights that challenges related to Models and Data often lack concrete solutions.”

“MedGemma-4b-it model, fine-tuned using Low-Rank Adaptation (LoRA), demonstrated superior diagnostic capability by achieving a mean test accuracy of 80.37% compared to 69.58% for the untuned GPT-4.”

“The context-aware model achieves a classification accuracy of 73.4%, dramatically outperforming context-agnostic versions (as low as 38.4%).”

“I need help collecting data which is partial AI and partially human written so I can finetune it, Any help is appreciated”

“The Simple Baseline for Multimodal Learning (SimBaMM) often performs comparably to, and sometimes outperforms, more complex architectures.”

“「スマホがあるということはClaudeアプリがあるじゃないか！」”

“The paper's core finding is that models fine-tuned with their prompt augmentation strategy maintain stable performance across diverse prompt patterns during inference and yield higher weighted F1 scores than those fine-tuned on a single prompt template.”

“BioSelectTune achieves state-of-the-art (SOTA) performance across multiple BioNER benchmarks. Notably, our model, trained on only 50% of the curated positive data, not only surpasses the fully-trained baseline but also outperforms powerful domain-specialized models like BioMedBERT.”

“State-of-the-art models often overfit to the training set and are evaluated using training, validation, and test sets that are not mutually exclusive.”

“RSA constructs candidate models via binomial random subset strategy and aggregates their predictions through a two-round weighting scheme, resulting in a structure analogous to a two-layer neural network.”

“The proposed method achieves superior transmission success rate, energy efficiency, and adaptability compared with the conventional UCB1-tuned algorithm without SIC.”

“The ALEAHallu framework follows an 'Activate-Locate-Edit Adversarially' paradigm, fine-tuning hallucination-prone parameter clusters using adversarial tuned prefixes to maximize visual neglect.”

“The article's core focus is on how hydrostatic pressure affects diffusioosmosis.”

“The proposed method matches or surpasses fine-tuned models on target words, improves general performance by about 5 BLEU, and mitigates catastrophic forgetting.”

“AgenticTCAD achieves the International Roadmap for Devices and Systems (IRDS)-2024 device specifications within 4.2 hours, whereas human experts required 7.1 days with commercial tools.”

“Scene-VLM yields significant improvements of +6 AP and +13.7 F1 over the previous leading method on MovieNet.”

“The idea is simple: frontier models are generalists, but a small model fine-tuned on domain-specific tool calling data can become a specialist that beats them at that specific task.”

“LFM2-2.6B-Exp is an experimental checkpoint built on LFM2-2.6B using pure reinforcement learning by Liquid AI”

“Fine-tuning significantly improves performance, with XLM-RoBERTa, mDeBERTa and MultilingualBERT achieving around 91% on both accuracy and F1-score.”

“Fine-tuned models show strong performance gains. ResNet18 achieves the highest accuracy of 79.17%, F1 score of 79.12%, AUC of 84.37% and EER of 24.35%.”

“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 high-field regime requires a new perspective, which we provide through a projected spin-1/2 framework built from Zeeman-selected crystal-field states not related by time reversal. This construction naturally allows emergent three-body interactions on triangular plaquettes and explains the asymmetric evolution of the fractional steps in the magnetization.”

“N/A”

“今年のクソアプリはこれでいこう (Let's make this year's bad app with this)”