As generic machine translation (MT) quality has improved, the need for targeted benchmarks that explore fine-grained aspects of quality has increased. In particular, gender accuracy in translation can have implications in terms of output fluency, tra...
Recent breakthroughs in diffusion models, multimodal pretraining, and efficient finetuning have led to an explosion of text-to-image generative models. Given human evaluation is expensive and difficult to scale, automated methods are critical for eva...
Using blockchain technology, it is possible to create contracts that offer a reward in exchange for a trained machine learning model for a particular data set. This would allow users to train machine learning models for a reward in a trustless manner...
When evaluating the ecological value of land use within a landscape, investigators typically rely on measures of habitat selection and habitat quality. Traditional measures of habitat selection and habitat quality require data from resource intensive...
We introduce AuditBench, an alignment auditing benchmark. AuditBench consists of 56 language models with implanted hidden behaviors. Each model has one of 14 concerning behaviors--such as sycophantic deference, opposition to AI regulation, or secret...
Experimental robot optimization often requires evaluating each candidate policy for seconds to minutes. The chosen evaluation time influences optimization because of a speed-accuracy tradeoff: shorter evaluations enable faster iteration, but are also...
Dec 12, 2025 · New research emphasizes the importance of well-validated models and forecasting tools in evaluating choices for investments in clean energy technologies and policies by governments and …
coordinating recalls, evaluating products that are the subject of consumer complaints or industry reports, etc.); developing uniform safety standards (some
Networks are essential for analyzing complex systems. However, their growing size necessitates backbone extraction techniques aimed at reducing their size while retaining critical features. In practice, selecting, implementing, and evaluating the mos...
May 30, 2025 · We analyse a range of Kodi builds to see which are best optimized for devices like the Amazon Firestick, evaluating appearance, user-friendliness, and more.
Visualisation of data is critical to understanding astronomical phenomena. Today, many instruments produce datasets that are too big to be downloaded to a local computer, yet many of the visualisation tools used by astronomers are deployed only on de...
Crafting quizzes from educational content is a pivotal activity that benefits both teachers and students by reinforcing learning and evaluating understanding. In this study, we introduce a novel approach to generate quizzes from Turkish educational t...
The assessment of evaluation metrics (meta-evaluation) is crucial for determining the suitability of existing metrics in text-to-image (T2I) generation tasks. Human-based meta-evaluation is costly and time-intensive, and automated alternatives are sc...
A beautiful, free online scientific calculator with advanced features for evaluating percentages, fractions, exponential functions, logarithms, trigonometry, statistics, and more.
One way of understanding wellbeing is how well people are able to flourish – whether they feel positive emotions, can function well in society, can respond to challenges and make meaning in their lives – …
Sources & verification Wall Street Journal report on Kalshi and Polymarket evaluating roughly $20 billion valuations (early-stage discussions). Kalshi’s December funding round and its stated valuation …
In statistical learning theory, the principle of empirical risk minimization defines a family of learning algorithms based on evaluating performance over
We introduce Cube Bench, a Rubik's-cube benchmark for evaluating spatial and sequential reasoning in multimodal large language models (MLLMs). The benchmark decomposes performance into five skills: (i) reconstructing cube faces from images and text,...
I’m not a Darden student. I’m an applicant who was seriously evaluating the program, so instead of relying on branding, I spoke directly with several current first years about day-to-day culture. ...
In recent years, multi-agent frameworks powered by large language models (LLMs) have advanced rapidly. Despite this progress, there is still a notable absence of benchmark datasets specifically tailored to evaluate their performance. To bridge this g...