“This model's impressive performance is particularly noteworthy.”

“If you enjoy this video, consider watching the other episodes in this universe for this video to make sense.”

“Llama-3.2-1B-4bit → 464 tok/s”

“It's not multimodal yet, but it does let you refine clarity, tone, and intent.”

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

“LLMs learn to predict the next word from a large amount of data.”

“MedGemma 1.5, small multimodal model for real clinical data MedGemma […]”

“Google Gen AI SDK is an official SDK that allows you to easily handle Google's Gemini models from Node.js, Python, Java, etc., supporting text generation, multimodal input, embeddings, and tool calls.”

“This series dissects the inner workings of LLMs, from full scratch implementations with Python and NumPy, to cutting-edge techniques used in Qwen-32B class models.”

“We also offer insights into potential future directions, including more advanced prompt engineering for large language models (LLMs) and expanding the scope of audio-based analysis to capture emotional cues that text data alone might miss.”

“”

“A team of Stanford Medicine researchers have introduced SleepFM Clinical, a multimodal sleep foundation model that learns from clinical polysomnography and predicts long term disease risk from a single night of sleep.”

“While security for text-based LLMs is an active area of research, existing solutions are often insufficient to address the unique threats for the embodied robotic agents, where malicious outputs manifest not merely as harmful text but as dangerous physical actions.”

“It’s built to power reliable on-device agentic applications: higher quality, lower latency, and broader modality support in the ~1B parameter class.”

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

“Gemini API のマルチモーダル機能を使った実装で、parts配列の構造について複数箇所でハマりました。”

“Recently, leveraging the complementary characteristics of SAR and MSI data through a multimodal approach has emerged as a promising strategy for advancing water extent mapping using deep learning models.”

“Latest research trends in architecture, efficiency, multimodal learning, reasoning ability, and safety.”

“N/A (Content is a pull request, not a paper or article with direct quotes)”

“I just launched Paper Breakdown, a platform that makes it easy to stay updated with CS/ML/AI research and helps you study any paper using LLMs.”

“The article quotes Wang Chen, the founder, stating that they believe financial investment is an important testing ground for AI technology.”

“"The good thing about Gemini is it's native multimodality. It can reason over the generated video and that iterative loop helps a lot and dealing with just one model and framework was super easy"”

“The article mentions the Nuremberg Chronicle, printed in 1493, is considered one of the most important illustrated books of the early modern period.”

“The key methodological innovation is that orthogonal complement projections completely eliminate cross-modal interference when estimating each loading space.”

“The paper presents its axiomatization that is sound with respect to the class of all fuzzy context models. In addition, both the necessity and sufficiency fragments of the logic are also individually complete with respect to the class of all fuzzy context models.”

“The bursts exhibit significant morphological diversity, including multiple sub-bursts, downward frequency drifts, and intrinsic widths ranging from 1.032 - 32.159 ms.”

“The paper argues that vibe coding is best understood as interface flattening, a reconfiguration in which previously distinct modalities (GUI, CLI, and API) appear to converge into a single conversational surface, even as the underlying chain of translation from intention to machinic effect lengthens and thickens.”

“The best-performing MLLM achieves only 58.0% accuracy.”

“The system automatically generates initial annotations, enables iterative model retraining, and incorporates data anonymization and domain adaptation techniques.”

“Enhancing the baseline agent with Chain-of-Thought (CoT) reasoning and self-reflection leads to an unexpected performance decrease, suggesting MLLMs exhibit poor context awareness in embodied navigation tasks.”

“The model achieves 12% median relative error using discovered semantic features from multimodal listing data, substantially outperforming a GPT-5 baseline (38% error).”

“Our algorithm enables off-the-shelf cross-modal systems trained on 2D visual inputs to adapt online to object occlusions and differentiate features.”

“The proposed method applies SSL comprehensively for both the architecture search and model pretraining processes.”

“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.”

“Sensor-only detection outperforms full fusion by 8.3 percentage points (93.08% vs. 84.79% F1-score), challenging the assumption that additional modalities invariably improve performance.”

“MDiffFR employs a tailored diffusion model on the server to generate embeddings for new items, which are then distributed to clients for cold-start inference.”

“The paper proposes a multi-modal cross-domain mixed fusion model with dual disentanglement for fault diagnosis.”

“The dataset incorporates 12K tactile-enhanced episodes and 20K mobile manipulation trajectories.”

“AudioFab's core contribution lies in offering a stable and extensible platform for future research and development in audio and multimodal AI.”

““...the first real-world large-scale multi-modal dataset for roadside-level 3D visual grounding.””

“HUMOR employs a hierarchical, multi-path Chain-of-Thought (CoT) to enhance reasoning diversity and a pairwise reward model for capturing subjective humor.”

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

“The Dermatology Assessment Schema (DAS) is a novel expert-developed framework that systematically captures clinically meaningful dermatological features in a structured and standardized form.”

“SenseNova-MARS achieves state-of-the-art performance on open-source search and fine-grained image understanding benchmarks. Specifically, on search-oriented benchmarks, SenseNova-MARS-8B scores 67.84 on MMSearch and 41.64 on HR-MMSearch, surpassing proprietary models such as Gemini-3-Flash and GPT-5.”

“SaM2B leverages lightweight cues such as environmental visual, flight posture, and geospatial data to adaptively allocate contributions across modalities at different time points through reliability-aware dynamic weight updates.”

“CERES implements dual-modal causal intervention: applying backdoor adjustment principles to counteract language representation biases and leveraging front-door adjustment concepts to address visual confounding.”

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

“The WiYH Dataset features over 1,000 hours of multi-modal manipulation data across hundreds of skills in diverse real-world scenarios.”

“FIGR improves the base model by 13.12% on AIME 2025 and 11.00% on BeyondAIME, highlighting the effectiveness of figure-guided multimodal reasoning in enhancing the stability and reliability of complex reasoning.”

“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.”