Open-vocabulary object detection (OVD) aims to detect arbitrary objects with user-provided text labels. Although recent progress has enhanced zero-shot detection ability, current techniques handicap themselves with three important challenges. They heavily depend on expensive and large-scale region-level annotations, which are hard to scale. Their captions are typically short and not contextually rich, which makes them… →
Developing AI systems that learn from their surroundings during execution involves creating models that adapt dynamically based on new information. In-Context Reinforcement Learning (ICRL) follows this approach by allowing AI agents to learn through trial and error while making decisions. However, this method has significant challenges when applied to complex environments with various tasks. It… →
CONCLUSIONS: This study supports the efficacy of a low-intensity psychological intervention applied in a blended format on multimorbidity in primary care. It justifies the exploration of the conceptualization of depression in type 2 diabetes as well as the analysis of the implementation of such interventions in routine clinical practice. →
CONCLUSIONS: The APPROACH intervention was successfully implemented and shows promise for increasing brisk walking, potentially through promoting habit formation and enabling self-monitoring. Contextual factors will be important to consider when interpreting outcomes in the larger APPROACH randomized controlled trial. →
CONCLUSION: Suction pressure levels during bronchial obstruction were predictive of BAL recovery rate failure, suggesting that a weak bronchial wall may be more prone to collapse under suction pressure. →
Text-to-speech (TTS) technology has made significant strides in recent years, but challenges remain in creating natural, expressive, and high-fidelity speech synthesis. Many TTS systems struggle to replicate the nuances of human speech, such as intonation, emotion, and accent, often resulting in artificial-sounding voices. Additionally, precise voice cloning remains difficult, limiting the ability to generate personalized… →
The International Mathematical Olympiad (IMO) is a globally recognized competition that challenges high school students with complex mathematical problems. Among its four categories, geometry stands out as the most consistent in structure, making it more accessible and well-suited for fundamental reasoning research. Automated geometry problem-solving has traditionally followed two primary approaches: algebraic methods, such as… →
Large language models (LLMs) must align with human preferences like helpfulness and harmlessness, but traditional alignment methods require costly retraining and struggle with dynamic or conflicting preferences. Test-time alignment approaches using reward models (RMs) avoid retraining but face inefficiencies due to reliance on trajectory-level rewards, which evaluate full responses rather than guiding token-by-token generation. Existing… →
Background: Sleep disturbances are highly prevalent in traumatized refugees and often persist despite treatment, and adapted scalable interventions are needed. The group intervention ‘Sleep Training adapted for Refugees’ (STARS) is a culturally- and context-sensitive approach based on evidence-based treatments for sleep disturbances (e.g. CBT-I, IRT). This study evaluated the feasibility, acceptability, and effectiveness of STARS.Method:… →
focused on patients living with metastatic cancer. We examined the feasibility of the SleepNow intervention combining cognitive behavioral therapy for insomnia (CBT-I) with physical exercise in men with metastatic prostate cancer (mPCa). →