Write the new Coact-1 from Salesforce

Computer use agents usually depend on The language of vision and Vision movement Models (VLMS or Vlas) to realize the screen and take action, Simulating how a person uses mouse and keyboard.

While these agents based on the graphic user interface can perform a variety of tasks, they are It often stumbles when facing a long complex workflow, especially in applications with lists and dense optionsLike office productivity suites.

For example, it can include the task that includes locating a specific schedule in a spreadsheet, filtering it, and saving it as a new and accurate sequence file from the process of processing the graphic user interface.

This is where fragility crawls. “In these scenarios, the current factors are often struggled with the ambiguity of visual grounding (for example, a distinction between visually similar symbols or menu elements) and the accumulated possibility of committing any one mistake on the long horizon,” researchers write in Determine them. “The wrong user interface element or whose understanding can be out of the entire important path.”

To face these challenges, many researchers have focused on increasing graphic user interface agents with high -level planners.

These systems use strong thinking models such as Openai’s O3 To analyze the high -level user’s goal into a series of smaller sub -tasks that can be controlled.

Although this organized approach improves performance, it does not solve the problem of navigation in the menus and clicking the buttons, even for the processes that can be done directly and reliable with a few lines of software instructions.

COACT-1: A multi-agent team for computer tasks

To solve these restrictions, researchers created Coact-1 (computer use agent with coding as procedures), A system designed to “combine intuitive strengths that resemble a person to treat the graphic user interface, accuracy, reliability and efficiency of the direct system interaction through the code.”

order Organized as a team of three specialized agents working together: Orkor, programmer and graphic user interface operator.

Orchestrator works as a central plan or project manager. It analyzes the user’s general goal, divides him into sub -tasks, and appoints every sub -task for the best agent of this job. It can delegate background operations such as file management or data processing to the programmer, which It writes and executes Python or text software.

For the front end Tasks that require clicking buttons or moving visible facades, they turn into a graphic user interface player, VLM agency.

“This dynamic delegation allows Coact-1 to exceed the strategic ineffective graphic interface sequence in favor of implementing the strong code and single code when necessary, while continuing to take advantage of the visual interaction of the indispensable tasks,” says the paper.

The workflow is a repetition. After the programmer or the user interface operator completes sub -tasks, it sends a summary and screenshot of the current system status to Orchestrator, which decides the next step or concludes the task.

The LLM programmer is used to create his code and send orders to a code translator to test his software instructions and improve them on multiple rounds.

Likewise, the graphic user interface operator uses a work translator who performs his orders (for example, mouse clicks, writing) and returning the resulting screen shot, allowing them to see the results of its actions. Orchestrator makes the final decision on whether the task should continue or stop.

A more efficient road to automation

The researchers tested Coact-1 on OsworldA comprehensive standard that includes 369 tasks in the real world via browsers, IDES, and office applications.

Results show COACT-1 creates the latest latest, achieving a success rate of 60.76 %.

Performance gains were the most important in categories where software control provides a clear advantage, such as OS level tasks and multi -applications.

For example, Consider the OS level, such as finding all the image files inside a complex folder brown, changing their size, then pressing the entire guide in one archive.

A The documented worker will need a purely graphic user interface to make a long -haired sequence of clicks and withdrawalOpen folders, choose files, and move in the menus, with a great chance of error in each step.

In contrast, Coact-1 can delegate the entire workflow to its programmer, which can accomplish the task through one strong text.

Beyond just a higher success rate, the system is greatly efficient. COACT-1 The tasks are on average 10.15 steps only, a blatant contrast with 15.22 step by the graphic user interface agents only such as GTA-1.

While other factors such as Openai’s Cua 4O were on average lower steps, their total success rate was much lower, indicating that Coact-1 efficiency is more effective.

The researchers found a clear trend: The tasks that require more procedures are likely to fail. Reducing the number of steps not only speeds up the completion of the task, but most importantly, it reduces the chances of error.

So, Finding ways to compress the multiple graphic user interface steps can lead to one software mission to make the process more efficient and less vulnerable to error.

The researchers also conclude, “This competence emphasizes the possibilities of our approach to paving a more powerful and developmental path towards a generalized computer automation.”

From the laboratory to the functioning of the institution

The possibility of this general productive technology exceeds. For institution leaders, the key is to automate complex multi -tools where the API full access is luxury and not a guarantee.

Ran Show, co -author of the paper and director of artificial intelligence research at Salesforce, refers to customer support as a major example.

“Service Support Agent uses many different tools-public tools such as Salesforce, industry tools such as Epic for Healthcare, and many custom tools-to investigate the customer’s request and formulate response,” said Xu Venturebeat. “Some tools have an access interface interface while not doing it. It is an ideal use that can benefit from our technology: An account use of an account that takes advantage of all available from the computer, whether it is an application programming interface, symbol or only on the screen. “

Xu also sees high -value applications in sales, such as size exploration, gossip automation, and marketing for tasks such as clients fragmentation and generating campaigns assets.

Mobility in the challenges of the real world and the need for human oversight

Although the results on the osworld standard are strong, institutions environments are more chaotic, full of old programs and an unpredictable user interface.

This raises critical questions about the durability, security and the need for human control.

The main challenge is to ensure that the Orchestrator agent chooses the right choice when facing an unfamiliar application. According to Xu, the way to create agents such as Coact-1 is strong for the designated institution’s programs that include training on comments in realistic environments and simulation.

The goal is to create a system “The agent can notice how human agents work, training within the sand box, and when he walks live, he continued to solve tasks under the supervision of a human agent.”

The ability of the programmer to implement its code provides clear security concerns. What prevents the agent from implementing a harmful symbol at the request of a mysterious user?

Show confirms that strong containment is necessary. He said: “Control of arrival and sand box is the key,” stressing that a person must “understand the effects of antiquities and grant artificial intelligence safety.”

Sand and handrails will be necessary to verify the validity of the agent Before publishing on critical systems.

In the end, in the foreseeable future, it is possible that the mystery is likely to be overpowered in the episode. When asked about dealing with mysterious user inquiries, he also suggested an occupant in the paper, following a deported approach. “I see that a person is in the episode to start,” he pointed out.

While some tasks may eventually become completely independent, checking human health will remain very important. “Some critical task may always need human approval.”

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