AINeutralarXiv – CS AI · May 286/10
🧠Researchers have developed a diffusion-based model for generating handwritten Ukrainian text with style transfer capabilities, addressing a significant gap in non-Latin script generation. By constructing a 126,177-image Ukrainian dataset and retraining DiffusionPen without architectural changes, the model demonstrates that few-shot latent diffusion generalizes beyond Latin scripts to Cyrillic writing systems.
AINeutralarXiv – CS AI · May 286/10
🧠Researchers introduce SMILE-Next, a comprehensive dataset and specialized large language model framework for understanding laughter in real-world contexts. The work combines laughter detection, classification, and reasoning tasks with novel training techniques including laughter-specific self-instruction and a mixture-of-experts architecture to improve multimodal language model performance on this underexplored domain.
AINeutralarXiv – CS AI · May 285/10
🧠Researchers introduce the Video Important Person (VIP) identification task and Temporal-VIP dataset to automatically identify key individuals in video scenes while addressing the Temporal Importance Shift phenomenon. The VIP-Net framework achieves 67.3% accuracy, significantly outperforming existing methods (37.5%-53.9%), with applications in automated video editing and intelligent surveillance.
🏢 Hugging Face
AINeutralarXiv – CS AI · May 286/10
🧠Researchers have released IPO-Toolkit and IPO-Dataset, a comprehensive open-source framework and dataset containing over 109,000 IPO filings from 1994-2026 with 76,000+ extracted images. The resource enables large-scale analysis of long, multimodal financial documents and reveals that state-of-the-art AI models often misalign with expert judgments on financial chart interpretation tasks.
AIBullisharXiv – CS AI · May 276/10
🧠Researchers introduce FAST-GOAL, a fine-tuning method that improves CLIP's ability to process lengthy text descriptions through global-local semantic alignment. The approach combines object detection with token-level similarity learning and introduces GLIT100k, a new dataset linking long captions to localized image-text pairs, demonstrating significant performance gains across multiple benchmarks.
AINeutralarXiv – CS AI · May 276/10
🧠Researchers introduce MeDial-Speech, a new 111+ hour speech dataset for training medical AI systems to conduct patient consultations across four health conditions. The study benchmarks state-of-the-art LLMs including Claude Sonnet 4, GPT-5 mini, and DeepSeek-V3, revealing that while Claude Sonnet 4 achieves 71-75% accuracy in medical dialogue tasks, all models exhibit significant overconfidence in their probabilistic predictions.
🏢 Hugging Face🧠 GPT-5🧠 Claude
AIBullisharXiv – CS AI · May 276/10
🧠Researchers have released ParsVoice, a 2,200-hour Persian speech dataset with 1.36 million aligned segments from 1,815 speakers, making it 25 times larger than previous Persian TTS resources. The dataset was constructed using an automated pipeline combining ASR, fine-tuned language models, and quality assessment, and validation shows the corpus enables multi-speaker text-to-speech systems competitive with existing solutions.
🏢 Hugging Face
AINeutralarXiv – CS AI · May 116/10
🧠Researchers introduce MIST, a synthetic dataset and framework for training voice-based AI assistants to control IoT devices in smart homes. The work reveals significant performance gaps between open and closed-weight multimodal LLMs on complex, real-world smart home tasks requiring spatiotemporal reasoning and mixed-initiative interaction.
AINeutralarXiv – CS AI · May 116/10
🧠Researchers introduce SAM 3D Animal, a promptable framework for reconstructing multiple animals in 3D from single images, addressing key challenges like occlusion and species variation. The team also releases Herd3D, a new multi-animal dataset with over 5K images, achieving state-of-the-art results across multiple benchmarks.
AINeutralarXiv – CS AI · Apr 156/10
🧠StableSketcher is a novel AI framework that enhances diffusion models for generating pixel-based hand-drawn sketches with improved prompt fidelity. The approach combines fine-tuned variational autoencoders with a reinforcement learning reward function based on visual question answering, alongside a new SketchDUO dataset of instance-level sketches paired with captions and Q&A pairs.
🧠 Stable Diffusion
AINeutralarXiv – CS AI · Mar 176/10
🧠Researchers released MALINT, the first human-annotated English dataset for detecting disinformation and its malicious intent, developed with expert fact-checkers. The study benchmarked 12 language models and introduced intent-based inoculation techniques that improved zero-shot disinformation detection across six datasets, five LLMs, and seven languages.
🧠 Llama
