Recently, preference optimization methods such as DPO have significantly enhanced large language models (LLMs) in wide tasks including dialogue and question-answering. However, current methods fail to account for the varying difficulty levels of training samples during preference optimization, leading to mediocre performance in tasks with high accuracy requirements, particularly in mathematical reasoning. To address this limitation, we propose a novel training framework, which employs multiple sampling to analyze output distributions, assign different weights to samples, and incorporate these weights into the preference optimization process. This plug-and-play approach enables LLMs to prioritize challenging examples during training, improving learning efficiency. Experimental results demonstrate that our framework integrates seamlessly with various preference optimization methods and achieves consistent improvements in mathematical reasoning tasks.

Neural ordinary differential equations (Neural ODEs) propose the idea that a sequence of layers in a neural network is just a discretisation of an ODE, and thus can instead be directly modelled by a parameterised ODE. This idea has had resounding success in the deep learning literature, with direct or indirect influence in many state of the art ideas, such as diffusion models or time dependant models. Recently, a continuous version of the U-net architecture has been proposed, showing increased performance over its discrete counterpart in many imaging applications and wrapped with theoretical guarantees around its performance and robustness. In this work, we explore the use of Neural ODEs for learned inverse problems, in particular with the well-known Learned Primal Dual algorithm, and apply it to computed tomography (CT) reconstruction.

Fox News Flash top sports headlines are here. Check out what's clicking on Foxnews.com. EC3 made his National Wrestling Alliance (NWA) debut at the company's 74th-anniversary show last year and a year later he defeated Tyrus for the Worlds Heavyweight Championship putting him on top of the historic promotion and ending the career of one of the most well-known performers in the business. Two months after capturing the title at the 75th-anniversary show, Thom Latimer used the "Lucky Seven Rule" to drop the NWA World Television Championship for a chance at EC3's title. The two will meet in a singles match at NWA Samhain later this month for the title. Better yet, EC3 gets to perform in front of his hometown fans in Cleveland, Ohio.

Kolkata: Now, bots and artificial intelligence too will join efforts to preserve the Gandhian legacy.

For years, the people developing artificial intelligence drew inspiration from what was known about the human brain, and it has enjoyed a lot of success as a result. Now, AI is starting to return the favor. Although not explicitly designed to do so, certain artificial intelligence systems seem to mimic our brains' inner workings more closely than previously thought, suggesting that both AI and our minds have converged on the same approach to solving problems. If so, simply watching AI at work could help researchers unlock some of the deepest mysteries of the brain. "There's a real connection there," said Daniel Yamins, assistant professor of psychology.

Artificial intelligence has been borrowing from the brain since its early days, when computer scientists and psychologists developed algorithms called neural networks that loosely mimicked the brain. Those algorithms were frequently criticized for being biologically implausible – the "neurons" in neural networks were, after all, gross simplifications of the real neurons that make up the brain. They just wanted systems that worked, so they extended neural network models in whatever way made the algorithm best able to carry out certain tasks, culminating in what is now called deep learning.

With the wave of personal assistants, such as Siri, Cortana and Google Assistant, and new start-ups leveraging artificial intelligence (AI) and analytics to build personal companions, it's becoming clear we are moving toward a new voice-controlled relationship with technology. As we have already seen in the consumer market, it is all but a given that these voice-activation systems will eventually make it into the enterprise environment, as the potential benefits of these systems could be tremendous in simplifying and automating activities. Here, Craig Walker, director Cloud Services at Alcatel-Lucent Enterprise, explains that, although it may be a long time before we see the full likenesses of "HAL" from "2001: A Space Odyssey", the technology is already here that can improve the ways businesses operate. Think how much easier it would be for a physician to just say "System: update Mary Smith's chart with the following: "Patient experiencing abdominal pain, issue pharmacy order for 200MG of'SuperAntiGas', signed Dr. FeelBetter." Or in a conference room, instead of the struggle to figure out which remote control puts on the projector and the screen, a simple voice request "System: turn on projector, turn on TV and dim lights."

With the wave of personal assistants, such as Siri, Cortana and Google Assistant, and new startups leveraging AI and analytics to build personal companions, it's becoming clear we are moving toward a new voice-controlled relationship with technology. As we have already seen in the consumer market, it is all but a given that these voice-activation systems will eventually make it into the enterprise environment, as the potential benefits of these systems could be tremendous in simplifying and automating activities. Although it may be a long time before we see the full likenesses of "HAL" from "2001: A Space Odyssey", the technology is already here that can improve the ways businesses operate. Think how much easier it would be for a physician to just say "System: update Mary Smith's chart with the following: "Patient experiencing abdominal pain, issue pharmacy order for 200MG of'SuperAntiGas', signed Dr. FeelBetter." Or in a conference room, instead of the struggle to figure out which remote control puts on the projector and the screen, a simple voice request "System: turn on projector, turn on TV and dim lights."

There has been a lot of activity recently around revenue attribution - marketers want to develop a better understanding of their customer acquisition funnel and be able to measure progress against it. Most of this attention has been focused on the B2C space. However, less work has been done measuring the performance of B2B marketing activities. While Salesforce is an excellent platform for managing leads and campaigns, their business model is founded on developing a sales and marketing ecosystem comprising partnerships with specialist vendors that can provide more focused solutions to specific sales and marketing issues. As a result, companies such as Full Circle Insights, Bright Funnel and Bizable have emerged to fill the void in B2B marketing attribution by leveraging the Salesforce platform.

There has been a lot of activity recently around revenue attribution - marketers want to develop a better understanding of their customer acquisition funnel and be able to measure progress against it. Most of this attention has been focused on the B2C space. However, less work has been done measuring the performance of B2B marketing activities. While Salesforce is an excellent platform for managing leads and campaigns, their business model is founded on developing a sales and marketing ecosystem comprising partnerships with specialist vendors that can provide more focused solutions to specific sales and marketing issues. As a result, companies such as Full Circle Insights, Bright Funnel and Bizable have emerged to fill the void in B2B marketing attribution by leveraging the Salesforce platform.