Large pretrained language models generate fluent text but are notoriously hard to controllably sample from. In this work, we study constrained sampling from such language models: generating text that satisfies user-defined constraints, while maintaining fluency and the model's performance in a downstream task. We propose MuCoLa -- a sampling procedure that combines the log-likelihood of the language model with arbitrary (differentiable) constraints in a single energy function, and then generates samples in a non-autoregressive manner. Specifically, it initializes the entire output sequence with noise and follows a Markov chain defined by Langevin Dynamics using the gradients of the energy function. We evaluate MuCoLa on text generation with soft and hard constraints as well as their combinations obtaining significant improvements over competitive baselines for toxicity avoidance, sentiment control, and keyword-guided generation.

While a substantial body of prior work has explored adversarial example generation for natural language understanding tasks, these examples are often unrealistic and diverge from the real-world data distributions. In this work, we introduce a two-stage adversarial example generation framework (NaturalAdversaries), for designing adversaries that are effective at fooling a given classifier and demonstrate natural-looking failure cases that could plausibly occur during in-the-wild deployment of the models. At the first stage a token attribution method is used to summarize a given classifier's behaviour as a function of the key tokens in the input. In the second stage a generative model is conditioned on the key tokens from the first stage. NaturalAdversaries is adaptable to both black-box and white-box adversarial attacks based on the level of access to the model parameters. Our results indicate these adversaries generalize across domains, and offer insights for future research on improving robustness of neural text classification models.

Mission teams are exposed to the emotional toll of life and death decisions. These are small groups of specially trained people supported by intelligent machines for dealing with stressful environments and scenarios. We developed a composite model for stress monitoring in such teams of human and autonomous machines. This modelling aims to identify the conditions that may contribute to mission failure. The proposed model is composed of three parts: 1) a computational logic part that statically describes the stress states of teammates; 2) a decision part that manifests the mission status at any time; 3) a stress propagation part based on standard Susceptible-Infected-Susceptible (SIS) paradigm. In contrast to the approaches such as agent-based, random-walk and game models, the proposed model combines various mechanisms to satisfy the conditions of stress propagation in small groups. Our core approach involves data structures such as decision tables and decision diagrams. These tools are adaptable to human-machine teaming as well.

Dr Asress Gikay argues that an outright ban on police use of live facial recognition technology would be a mistake. UK police are being accused of breaking ethical standards by using live facial recognition technology to help fight crime. A recent report by the University of Cambridge into trials of the technology by forces in London and South Wales was particularly concerned about the "lack of robust redress" for anyone suffering harm. It spoke of the need to "protect human rights and improve accountability" before facial recognition is used more widely. The Cambridge team wants a broad ban on police using the technology, and they are not alone.

Fox News national correspondent Bryan Llenas has the latest as Pennsylvania senate nominees make last plea to voters ahead of Tuesday's midterm elections. The balance of power in Washington, D.C., may not be settled when Election Day comes to an end – or the day after, or the day after that, depending on how things go in Pennsylvania. The Senate race between Democrat John Fetterman and Republican Dr. Mehmet Oz remained a toss-up in the final Fox News Power Rankings before Election Day, and litigation over absentee ballots could draw the process out well beyond November 8. The state's supreme court ruled that undated and incorrectly dated absentee ballots had to be set aside, uncounted, and federal litigation related to this remains ongoing. During a press conference on Monday, Pennsylvania Acting Secretary of State Leigh M. Chapman confirmed that voters worried that they already made mistakes may not be able to fix them.

Shocking drone footage shows migrants streaming across the U.S.-Mexico border into Eagle Pass, Texas, virtually unimpeded. The footage, captured by Fox News with thermal imaging cameras, is just one example of the daily mass crossings reporter Bill Melugin has witnessed at the border over the past week. Border crossings have surged under President Biden, and multiple migrants told Fox that "Joe Biden es el major," or "Joe Biden is the best." Melugin says the border crossings happen every morning "with no resistance" on either side of the border. Biden's administration has insisted that the U.S.-Mexico border is "closed" despite overwhelming evidence to the contrary. Illegal immigrants in a single file line after driver is busted by DPS officers.

Fox News' senior foreign affairs correspondent Greg Palkot reports from Kyiv on how Ukrainians are coping under Russian drone and missile attacks. KYIV, Ukraine - A "cold" war is building here in Ukraine at the hands of Vladimir Putin. As their progress slows on the battle front, Russian forces have been targeting civilian infrastructure. With winter closing in, and power, heat and water going, it could be Moscow's most dangerous tactic. "Militarily it's absolutely nothing," Ukrainian Member of Parliament Oleksiy Goncharenko explained, "but yes, it can cause a lot of suffering for civilians."

Gerasim Hovhannisyan, CEO and Co-Founder at EasyDMARC, a rapidly growing B2B SaaS to solve email security and deliverability problems. In part, because hybrid and remote workplaces are the new normal for most companies, the sophistication of cyberattacks and the risks they pose have grown rapidly over the last few years. In fact, these new work styles have opened up a whole new set of phishing methods for threat actors. According to Cybersecurity Ventures, global cybercrime is expected to grow by 15% per year over the next five years, costing about $10.5 billion by 2025. Even though hundreds of IT experts analyze threats daily, it is a daunting task.

Elon Musk has a lot going on right now. In the week since he bought Twitter for $44 billion, he fired its upper management and laid off thousands of employees, declared himself CEO and sole director, and used tweets and memes to publicly thrash out a dubious business plan that involves charging users $8 a month for benefits that include a blue check mark. All that is just Musk's new side gig. The world's richest man is perhaps now its busiest, revamping Twitter while also serving as CEO of electric-auto maker Tesla; rocket maker SpaceX; the Boring Company, which digs tunnels for transit; and Neuralink, which is testing brain implants meant to eventually connect humans with computers. How does Musk manage and lead all those complex projects at the same time?

A Bachelor's Degree in Computer Science or in a related technical field is highly desired which will be considered equivalent to two (2) years of experience A Master's degree in a Technical Field will be considered equivalent to four (4) years of experience A degree in Mathematics, Information Systems, Engineering, or similar degree will be considered as a technical field Eight (8) years of experience in software development/engineering, including requirements analysis, software development, installation, integration, evaluation, enhancement, maintenance, testing, and problem diagnosis/resolution and at least six (6) years of experience developing software with high level languages such as Java, C, C Demonstrated ability to work with OpenSource (NoSQL) products that support highly distributed, massively parallel computation needs such as Hbase, Acumulo, Big Table, etcAd: Ready to find your dream job? Use this free career assessment test to figure it out. Peraton drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted and highly differentiated national security solutions and technologies that keep people safe and secureAd: Stop spending hours editing your resume to fit job descriptions. Peraton serves as a valued partner to essential government agencies across the intelligence, space, cyber, defense, civilian, health, and state and local markets Every day, our employees do the can't be done, solving the most daunting challenges facing our customers For Colorado Residents: Colorado Salary Minimum: $90,500 Colorado Salary Maximum: $219,700 The estimate displayed represents the typical salary range for this position, and is just one component of Peraton's total compensation package for employees Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards In addition, Peraton provides a variety of benefits to employees