Large language models (LLMs) use extensive computational resources to process and generate human-like text. One emerging technique to enhance reasoning capabilities in LLMs is test-time scaling, which dynamically allocates computational resources during inference. This approach aims to improve the accuracy of responses by refining the model’s reasoning process. As models like OpenAI’s o1 series introduced… →
Hypothesis validation is fundamental in scientific discovery, decision-making, and information acquisition. Whether in biology, economics, or policymaking, researchers rely on testing hypotheses to guide their conclusions. Traditionally, this process involves designing experiments, collecting data, and analyzing results to determine the validity of a hypothesis. However, the volume of generated hypotheses has increased dramatically with the… →
CONCLUSIONS: US-guided TPVB had a higher success rate of upper extremity sympathetic blockade than US-guided SGB, with more pronounced immediate postprocedural pain relief. →
CONCLUSIONS: The PACU-SLA revealed lower fluency (hypophonia) with relatively intact comprehension, naming, and repetition, during recovery from general anesthesia. These deficits share features with transcortical motor aphasia. →
Omaveloxolone is approved for the treatment of Friedreich ataxia (FA) in patients aged ≥ 16 years at a dose of 150 mg once daily. This double-blind, randomized, placebo- and active-controlled, three-way crossover, thorough corrected QT interval (QTc) study (NCT05927649) evaluated the effect of supratherapeutic omaveloxolone exposure on QTc to exclude a clinically significant prolongation (defined… →
Modern AI systems have made significant strides, yet many still struggle with complex reasoning tasks. Issues such as inconsistent problem-solving, limited chain-of-thought capabilities, and occasional factual inaccuracies remain. These challenges hinder practical applications in research and software development, where nuanced understanding and precision are crucial. The drive to overcome these limitations has prompted a reexamination… →
Vision‐language models (VLMs) have long promised to bridge the gap between image understanding and natural language processing. Yet, practical challenges persist. Traditional VLMs often struggle with variability in image resolution, contextual nuance, and the sheer complexity of converting visual data into accurate textual descriptions. For instance, models may generate concise captions for simple images but… →
Ideation processes often require time-consuming analysis and debate. What if we make two LLMs come up with ideas and then make them debate about those ideas? Sounds interesting right? This tutorial exactly shows how to create an AI-powered solution using two LLM agents that collaborate through structured conversation. For achieving this we will be using… →