Emotion recognition from video involves many nuanced challenges. Models that depend exclusively on either visual or audio signals often miss the intricate interplay between these modalities, leading to misinterpretations of emotional content. A key difficulty is reliably combining visual cues—such as facial expressions or body language—with auditory signals like tone or intonation. Many existing systems… →
Long-horizon robotic manipulation tasks are a serious challenge for reinforcement learning, caused mainly by sparse rewards, high-dimensional action-state spaces, and the challenge of designing useful reward functions. Conventional reinforcement learning is not well-suited to handle efficient exploration since the lack of feedback hinders learning optimal policies. This issue is significant in robotic control tasks of… →
In this tutorial, we implement a Bilingual Chat Assistant powered by Arcee’s Meraj-Mini model, which is deployed seamlessly on Google Colab using T4 GPU. This tutorial showcases the capabilities of open-source language models while providing a practical, hands-on experience in deploying state-of-the-art AI solutions within the constraints of free cloud resources. We’ll utilise a powerful… →
Large language models (LLMs) models primarily depend on their internal knowledge, which can be inadequate when handling real-time or knowledge-intensive questions. This limitation often leads to inaccurate responses or hallucinations, making it essential to enhance LLMs with external search capabilities. By leveraging reinforcement learning, researchers are actively working on methods to improve these models’ ability… →
Transformers have revolutionized natural language processing as the foundation of large language models (LLMs), excelling in modeling long-range dependencies through self-attention mechanisms. However, as these models grow deeper and more complex, training stability presents a significant challenge that directly impacts performance. Researchers face a troublesome trade-off between two primary normalization strategies: Pre-Layer Normalization (Pre-Norm) and… →
CONCLUSIONS: Intensive therapy based on a high cytarabine dose and continuously administered EDOCH achieved a high MRD-negative rate and provides an optional induction choice for young patients with MCL with high-risk factors. →
BACKGROUND: Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide, often diagnosed at an advanced stage with a poor prognosis. Paclitaxel, nab-paclitaxel, and irinotecan, either as monotherapies or in combination with ramucirumab, are currently standard second-line treatments for GC. However, the efficacy of these therapies is limited, necessitating the development of new… →
CONCLUSIONS: Based on this multicentre study about ENI, the incidence of interruptions in enteral nutrition was 18.6%, with diagnostic and therapeutic procedures being the leading causes. The occurrence of interruptions in the delivery of enteral nutrition leads to a reduction in the nutritional intake of critically ill patients. →
CONCLUSIONS: Compared to Coulter and QBC®, mean HemoCue® measured Hb concentrations were lower and, compared to the Coulter or QBC® methods, had an overall tendency to measure lower Hb concentrations with increasing Hb concentrations. Upper and lower limits of agreement were wider than the predefined clinically acceptable limits of ± 0.5 g/dL. HemoCue® should be… →
CONCLUSIONS: Even though the effects of NAC were observed in lowering the duration of the period and decreasing the frequency of bowel movements in gastroenteritis, these results did not reach statistical significance. Hence, the data from this study suggest that NAC may not effectively reduce the duration of diarrhea and the frequency of bowel movements… →