Language models (LMs) have gained significant prominence in computational text analysis, offering enhanced accuracy and versatility. However, a critical challenge persists: ensuring the validity of measurements derived from these models. Researchers face the risk of misinterpreting results, potentially measuring unintended factors such as incumbency instead of ideology, or party names rather than populism. This discrepancy…
As LLMs become increasingly complex and powerful, their inference process, i.e., generating text given a prompt, becomes computationally expensive and time-consuming. Many applications, such as real-time translation, dialogue systems, or interactive content generation, require quick responses. Additionally, slow inference consumes substantial computational resources, leading to higher operational costs. Researchers from the Dalian University of Technology,…
Large Multimodal Models (LMMs) are rapidly advancing, driven by the need to develop artificial intelligence systems capable of processing and generating content across multiple modalities, such as text and images. These models are particularly valuable in tasks that require a deep integration of visual and linguistic information, such as image captioning, visual question answering, and…
Large language models (LLMs) have demonstrated the ability to generate generic computer programs, providing an understanding of program structure. However, it is challenging to find the true capabilities of LLMs, especially in finding tasks they did not see during training. It is crucial to find whether LLMs can truly “understand” the symbolic graphics programs, which…
The application of RL to problems in complex decision-making, particularly in situations with limited resources and uncertain outcomes, has recently become very useful. In the varied applications of RL, what distinguishes Restless Multi-Arm Bandits (RMABs) is their solution to multi-agent resource allocation problems. RMAB models depict the management of several decision points or “arms,” each…
The multi-scale difficulty of designing new alloys calls for a comprehensive strategy, as this procedure includes gathering pertinent information, using advanced computational methods, running experimental validations, and carefully examining the results. Because the tasks involved in this complex workflow are intricate, it has traditionally taken a lot of time and was mostly completed by human…
Hardware manufacturers must follow rules and regulations called “hardware safety compliance” to ensure their goods aren’t harmful to people or the environment. Typical areas covered by these rules include product design, production, testing, and labeling, though they differ by country and sector. The existing approaches to ensuring hardware safety compliance have several things that could…
Accurately modeling nonlinear dynamical systems using observable data remains a significant challenge across various fields such as fluid dynamics, climate science, and mechanical engineering. Traditional linear approximation methods often fall short in capturing the complex behaviors exhibited by these systems, leading to inaccurate predictions and ineffective control strategies. Addressing this challenge is crucial for advancing…
The evaluation of legal knowledge in large language models (LLMs) has primarily focused on English-language contexts, with benchmarks like MMLU and LegalBench providing foundational methodologies. However, the assessment of Arabic legal knowledge remained a significant gap. Previous efforts involved translating English legal datasets and utilizing limited Arabic legal documents, highlighting the need for dedicated Arabic…
Deep learning models typically represent knowledge statically, making adapting to evolving data needs and concepts challenging. This rigidity necessitates frequent retraining or fine-tuning to incorporate new information, which could be more practical. The research paper “Towards Flexible Perception with Visual Memory” by Geirhos et al. presents an innovative solution that integrates the symbolic strength of…