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Efficacy and Safety of Dulaglutide Biosimilar LY05008 Versus the Reference Product Dulaglutide (Trulicity) in Chinese Adults With Type 2 Diabetes Mellitus: A Randomized, Open-Label, Active Comparator Study
CONCLUSION: The primary endpoint was met in this study through the demonstration of equivalent efficacy in HbA1c reduction in Chinese adults with T2DM between LY05008 and dulaglutide. Overall, the biosimilar product LY05008 showed comparable safety, PK, and immunogenicity profiles against the reference drug dulaglutide. →
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Benefits of Adding a Psychomotor Therapy Over a Combined-Approach Treatment in Adults who Stutter: A Randomized Controlled Trial
CONCLUSIONS & IMPLICATIONS: This randomized controlled trial did not demonstrate any benefit of adding a psychomotor therapy over a standard combined-approach treatment in young AWS. →
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3D-Printed anterior repositioning splint versus stabilization splint for patients with anterior disc displacement with reduction: A randomized cross-over clinical trial
CONCLUSION: Within the limitations of this study, both splints are considered reliable treatment options for patients with anterior disc displacement. The ARS initially demonstrated a greater improvement in pain compared to the SS. However, after the 3-month follow-up period, no significant difference was observed between the two splints. →
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Can LLMs Debug Like Humans? Microsoft Introduces Debug-Gym for AI Coding Agents
Can LLMs Debug Like Humans? Microsoft Introduces Debug-Gym for AI Coding Agents The Debugging Problem in AI Coding Tools Despite significant progress in code generation and completion, AI coding tools continue to face challenges in debugging—an integral part of software development. While large language models (LLMs) can generate code snippets and occasionally offer fixes, they… →
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This AI Paper from Salesforce Introduces VLM2VEC and MMEB: A Contrastive Framework and Benchmark for Universal Multimodal Embedd…
This AI Paper from Salesforce Introduces VLM2VEC and MMEB: A Contrastive Framework and Benchmark for Universal Multimodal Embeddings Multimodal embeddings combine visual and textual data into a single representational space, enabling systems to understand and relate images and language meaningfully. These embeddings support various tasks, including visual question answering, retrieval, classification, and grounding. The technology… →
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LLMs No Longer Require Powerful Servers: Researchers from MIT, KAUST, ISTA, and Yandex Introduce a New AI Approach to Rapidly Co…
LLMs No Longer Require Powerful Servers: Researchers from MIT, KAUST, ISTA, and Yandex Introduce a New AI Approach to Rapidly Compress Large Language Models without a Significant Loss of Quality HIGGS — the innovative method for compressing large language models was developed in collaboration with teams at Yandex Research, MIT, KAUST and ISTA. HIGGS makes… →
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Nvidia Released Llama-3.1-Nemotron-Ultra-253B-v1: A State-of-the-Art AI Model Balancing Massive Scale, Reasoning Power, and Effi…
Nvidia Released Llama-3.1-Nemotron-Ultra-253B-v1: A State-of-the-Art AI Model Balancing Massive Scale, Reasoning Power, and Efficient Deployment for Enterprise Innovation As AI adoption increases in digital infrastructure, enterprises and developers face mounting pressure to balance computational costs with performance, scalability, and adaptability. The rapid advancement of large language models (LLMs) has opened new frontiers in natural language… →
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The efficacy of methylprednisolone acetate nanogel in treating patients with sudden sensorineural hearing loss
Intratympanic injection of methylprednisolone acetate is considered to be one of the effective drugs in the treatment of sudden sensorineural hearing loss. In this study, the efficacy of intratympanic injection of methylprednisolone acetate nanogel in patients with sudden sensorineural hearing loss was investigated. It is a double-blind randomized clinical trial in one of Iran’s hospitals.… →
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Balancing Accuracy and Efficiency in Language Models: A Two-Phase RL Post-Training Approach for Concise Reasoning…
Balancing Accuracy and Efficiency in Language Models: A Two-Phase RL Post-Training Approach for Concise Reasoning Recent advancements in LLMs have significantly enhanced their reasoning capabilities, particularly through RL-based fine-tuning. Initially trained with supervised learning for token prediction, these models undergo RL post-training, exploring various reasoning paths to arrive at correct answers, similar to how an… →
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RoR-Bench: Revealing Recitation Over Reasoning in Large Language Models Through Subtle Context Shifts…
RoR-Bench: Revealing Recitation Over Reasoning in Large Language Models Through Subtle Context Shifts In recent years, the rapid progress of LLMs has given the impression that we are nearing the achievement of Artificial General Intelligence (AGI), with models seemingly capable of solving increasingly complex tasks. However, a fundamental question remains: Are LLMs genuinely reasoning like… →
