The reliable application of deep learning models to software engineering tasks hinges on high-quality training data. Yet, large-scale repositories inevitably introduce noisy or mislabeled examples that degrade both accuracy and robustness. While Noise Label Learning (NLL) has been extensively studied in other fields, there are a few works that investigate NLL in Software Engineering (SE) and Large Language Models (LLMs) for SE tasks. In this work, we propose MANTRA, a Multi-stage Adaptive Noise TReAtment framework that embeds noise diagnosis and mitigation directly into the fine-tuning process of code-Pretrained Language Models (PTM) and code-LLMs. We first investigate the effect of noise at varying levels on convergence and loss trajectories of the models. Then we apply an adaptive dropout strategy guided by per-sample loss dynamics and Gaussian Mixture Model clustering to exclude persistently noisy points while preserving clean data. Applying to code summarization and commit intent classification, our experiments reveal that some LLMs are more sensitive to noise than others. However, with MANTRA, the performance of all models in both tasks is improved. MANTRA enables researchers and practitioners to reduce the impact of errors introduced by the dataset in training, saves time in data cleaning and processing, while maximizing the effect of fine-tuning.

This paper presents a case study in the use of a large language model to generate a fictional Buddhist "sutra"', and offers a detailed analysis of the resulting text from a philosophical and literary point of view. The conceptual subtlety, rich imagery, and density of allusion found in the text make it hard to causally dismiss on account of its mechanistic origin. This raises questions about how we, as a society, should come to terms with the potentially unsettling possibility of a technology that encroaches on human meaning-making. We suggest that Buddhist philosophy, by its very nature, is well placed to adapt.

A reliable long-term time-series forecaster is highly demanded in practice but comes across many challenges such as low computational and memory footprints as well as robustness against dynamic learning environments. This paper proposes Meta-Transformer Networks (MANTRA) to deal with the dynamic long-term time-series forecasting tasks. MANTRA relies on the concept of fast and slow learners where a collection of fast learners learns different aspects of data distributions while adapting quickly to changes. A slow learner tailors suitable representations to fast learners. Fast adaptations to dynamic environments are achieved using the universal representation transformer layers producing task-adapted representations with a small number of parameters. Our experiments using four datasets with different prediction lengths demonstrate the advantage of our approach with at least $3\%$ improvements over the baseline algorithms for both multivariate and univariate settings. Source codes of MANTRA are publicly available in \url{https://github.com/anwarmaxsum/MANTRA}.

Rep. Wesley Hunt, R-Texas, responds to the U.S. conducting airstrikes after an American was killed in Syria and pushes back on'woke' agendas infiltrating the armed forces. Rep. Wesley Hunt, R-Texas, slammed the Biden administration on "Fox & Friends" Friday for abandoning the "peace through strength" mantra after an American was killed in an Iranian drone strike in Syria. WESLEY HUNT: I think what we're seeing right now is we are not serious people and our military is not being respected. This is also the same regime that wants to give Iran a nuclear weapon. So you look at what's happening in Iran and you look at what's happening in Syria, you're looking at what's happening in the Ukraine.

First, if you're a solver of the Mephisto series – which is unusual in giving the actual names of its setters – and have wondered what Paul McKenna does when he's not setting, you can now find out. The same setter is the Financial Times' Jason, and that paper interviews him as part of "an occasional series": Did your school mention crossword compiling in career discussions? It was never mentioned as a career option. I am a construction manager in the oil and gas pipeline industry. It is still a rare event for us to welcome a new compiler to the series.

We propose a novel model agnostic data-driven reliability analysis framework for time-dependent reliability analysis. The proposed approach -- referred to as MAntRA -- combines interpretable machine learning, Bayesian statistics, and identifying stochastic dynamic equation to evaluate reliability of stochastically-excited dynamical systems for which the governing physics is \textit{apriori} unknown. A two-stage approach is adopted: in the first stage, an efficient variational Bayesian equation discovery algorithm is developed to determine the governing physics of an underlying stochastic differential equation (SDE) from measured output data. The developed algorithm is efficient and accounts for epistemic uncertainty due to limited and noisy data, and aleatoric uncertainty because of environmental effect and external excitation. In the second stage, the discovered SDE is solved using a stochastic integration scheme and the probability failure is computed. The efficacy of the proposed approach is illustrated on three numerical examples. The results obtained indicate the possible application of the proposed approach for reliability analysis of in-situ and heritage structures from on-site measurements.

Do you have any favorite internal affirmations or mantras you like to offer students to help them feel confident in the face of potential bullies or put-downs? I'm trying to help out my elementary schooler. Right now I'm thinking of sayings along the lines of "I am awesome just as I am," or "I will not let others define me." Additionally, if there are any great all-purpose verbal comebacks or responses that might be applied generally, those would be helpful and welcome as well. Really, I welcome any suggestions you have for helping my child muster up confidence (with kindness). I speak to my students about this all the time.

Staff at the Mantra on Fort Street in Victoria take pride in their sumptuous lunch buffet. With different vegetarian and nonvegetarian curries offered every day, regular customers can look forward to a variety of dining options. Mantra on Fort Street also has a mechanical device that delivers drinks, cutlery, and other goodies to diners. It's a creation of GreenCo Robots, an Edmonton-based company headed by engineer Liang Yu. In a phone interview with the Straight, he said that about 30 of his firm's robots are in use across Canada.

It was soon evident that embracing digital technologies and using AI-driven analytics was the only way to remain buoyant and navigate the disruptions. Several companies worldwide have already transitioned to the work-from-home concept and have adapted to the modern distributed work ecosystem (See: How is digital transformation shaping the new future?). For CIOs, realigning priorities and accelerating enterprise innovations continue to be a roller-coaster experience amidst these unprecedented times. More and more enterprises are now leaning on data science and analytics to optimize business performance and drive growth. With virtual communication taking the center stage, there is a growing emphasis on implementing AI-based workforce analytics and business intelligence solutions to fast-track digital transformation and generate deeper operational insights to respond faster and steer the volatile economic landscape.

Legend has a prominent tale about a man who caught a large fish and kept it in a big tank filled with a lot of tiny fish. Over a few days, he observed that it was very easy for the big fish to catch the smaller ones and eat them. In due course of time, he partitioned the tank with a glass, in such a way that the big fish remains on one side of the glass, and the smaller ones on the other side. He noticed that the big fish tried hard over the first few days to catch its prey but failed to do so due to a glass partition. The man eventually removed the glass partition after a week and noticed that the big fish had stopped trying to hunt its prey.