How I Turned a Research Paper Into a Diagram, a Summary, and a Slide Deck With AI

Same files, one workspace, and a second opinion from ChatGPT, Claude, and Gemini before the deck went out.I needed to turn a research paper into a diagram, a summary, and a slide deck. Paper in. Diagram, summary, and slides out. Same source files, one workspace, and a second look from more than one…

Same files, one workspace, and a second opinion from ChatGPT, Claude, and Gemini before the deck went out.I needed to turn a research paper into a diagram, a summary, and a slide deck. Paper in. Diagram, summary, and slides out. Same source files, one workspace, and a second look from more than one model before I trusted the deck.I ran the whole sequence in HaloMate. It combines multiple AI models with persistent project files and specialized assistants called Mates. Each Mate can have its own instructions and isolated memory, which helps prevent unrelated context from leaking into the wrong project.Here is the sequence I actually ran: a diagram, a summary, a second look from ChatGPT, Claude, and Gemini, then a slide deck from the same files.Let’s get started.What I used instead of three chat appsI ran this in HaloMate. It is a cloud-based AI workspace built around persistent assistants called Mates.It brings model families such as GPT, Claude, Gemini, DeepSeek, and Grok into one interface, then adds separate memories, project files, research tools, and a working environment that can produce documents instead of stopping at a text response.What I actually used for this paper:Multi-model chat: Switch models during a conversation or compare responses side by side without rebuilding the prompt in another app.Personal AI Mates: Create specialized assistants with their own instructions, roles, and isolated memories, or start with a prebuilt Mate from the Mate Hub.Persistent files and projects: Keep PDFs, documents, spreadsheets, images, code, conversations, and generated outputs together, with file version history and recovery.Research and file creation: Search the web and academic sources, generate diagrams, analyze data, and create editable Word, Excel, PowerPoint, and PDF files within the chat workflow.To get started, head over to HaloMate and sign in.HaloMate homepage. Image by Jim Clyde MongeOnce you are inside, the dashboard feels immediately familiar.HaloMate main dashboard. Image by Jim Clyde MongeThere is a message box, a conversation area, and the usual expectation that I can type a question and get an answer within seconds. That familiarity helps. I did not have to learn a strange canvas before I could do anything useful.I skipped the warm-up questions and went straight to the project: a presentation on large language models. Before anything else, I had to pick a model.The model selector gives access to several major model families instead of locking the conversation to one provider.I can use a large reasoning model for a difficult explanation, move to a smaller and cheaper model for a quick rewrite, or ask another model to challenge the first answer. I can also adjust the reasoning effort when the task justifies the extra time and credit use.HaloMate AI model selection. Image by Jim Clyde MongeBefore touching the paper, I set up who would do the work. That is where Mates come in.A Mate is a reusable AI assistant configured for a particular job. A Mate is persona plus memory, not a prompt paired with a model. The model is only the engine for that turn. I can switch models and keep the same assistant.I can create one Mate for technical writing, another for presentation design, and another for personal research. Each can remember the instructions and preferences relevant to its job without dragging unrelated context into the next assignment.I do not have to keep telling a diagram assistant that I prefer readable labels. I also do not need to remind a writing assistant about the audience and tone every time I open a new chat.How I turned the paper into a diagramTo explore the prebuilt options, I opened the Mate Hub and looked for something that matched my project.I was preparing a presentation about LLMs and needed a clear diagram showing how model training works. Instead of prompting a general assistant and hoping it chose the right visual format, I selected the Architecture Diagrams Mate.HaloMate Mate Hub screen. Image by Jim Clyde MongeFor the text prompt, I used this:Prompt: Explain to me in a diagram how LLM training worksHaloMate illustration creation example. Image by Jim Clyde MongeA few seconds later, I had a well-illustrated overview that was much closer to presentation-ready than the usual wall of text.The flow was easy to follow, the stages were labeled, and I could download the result in multiple formats. Pretty cool, right?I still checked the wording and sequence because diagrams can make an error look finished. I would rather start from something concrete to improve instead of a blank slide.I could also create a custom Mate for this presentation and keep using it as the deck evolved. I would give it the audience, learning goals, preferred visual style, and required level of technical detail. The next diagram would begin with that context already in place.This is personalization at the project level, which is more useful to me than a single global memory trying to infer what every future conversation needs.How I summarized the research paper without starting overFiles follow the same persistent idea.HaloMate accepts PDFs, spreadsheets, documents, images, and code, but it treats them as part of a file system rather than a temporary attachment tied to one answer.A Mate can search across the files, use them as a knowledge base, create new versions, and keep generated outputs with the project. If an edit goes wrong, the version history provides a path back.For another test, I uploaded a research paper and asked for a summary.The experience was similar to other AI chat apps at first: attach a file, enter a request, and wait for the response.ChatGPT can summarize a PDF too. The difference was what I could do next without starting over. The paper stayed in the project as a file, not a one-off attachment. The summary sat next to it. When I wanted another model to check the summary, and later when I asked for slides, I pointed at the same files. I did not re-upload the PDF or rebuild the prompt three times.HaloMate paper summary example. Image by Jim Clyde MongeHow I got a second opinion from ChatGPT, Claude, and GeminiI also stayed in the same workspace and ran one question through Claude, GPT, and Gemini. Same project files. Same prompt. Three answers, side by side. I wanted to see whether another model would catch a hole the first one missed.One question, three models, side by side. Image by Jim Clyde MongeUploading the paper also made me look at where the request actually runs. Under Privacy & Compliance there is a Regions setting for model hosting: Mainland China, Singapore, and the United States. You can leave all three on or turn some off. The product warns that restricting regions may increase credit use and make some models unavailable. I left all three on for this test. It is a control I can see and change, not a privacy slogan.HaloMate Regions setting. Image by Jim Clyde MongeHow I turned the same paper into a slide deckThe last part of my test brought the workflow together.My LLM presentation included a section on knowledge distillation, and I needed more than a diagram. I wanted a short deck explaining how a larger teacher model transfers useful behavior to a smaller student model, why teams use the technique, and what can be lost during the process.I uploaded my reference material and asked HaloMate to create the presentation.The app recognized the file-creation request and routed the task to the appropriate capability. Instead of returning an outline for me to paste into PowerPoint, it generated an actual presentation file I could open. One slide laid out the teacher / student trade-off, which was the point of that section. I did not have to leave the chat to get a real pptx.HaloMate presentation slides example. Image by Jim Clyde MongeWithin seconds, I had a 10-slide deck on knowledge distillation.I would not present it without review. Slide generators can oversimplify technical details, repeat the same layout, or place too much confidence in a neat diagram.I checked the claims, adjusted the density, and made sure the story matched the audience.Even with that editing, the time savings were significant. The slowest part of presentation work is often getting from scattered notes to a coherent first version.HaloMate handled that blank-slide stage, kept the sources close to the project, and gave me a file I could continue editing.When a PDF-to-PPT converter is enoughIf all I needed was PDF to PPT, a dedicated converter or NotebookLM would have been enough. I used this because the job was bigger than a one-off conversion. The paper, the diagram, the summary, and the deck all lived in the same project, and they kept building on each other as the conversation went on. That is the part a converter cannot do.Who this workflow is forHaloMate is a good fit for researchers, technical writers, students, consultants, and creators who use AI for projects that last longer than one conversation. Its persistent files and isolated Mate memories reduce the need to upload the same material or repeat the same instructions.It also makes sense for people who regularly switch between ChatGPT, Claude, Gemini, and other models. HaloMate brings those models into one workspace, so I can pick a model for each task.If your work has to stay in a particular country, check the Regions setting before you upload the file. Restricting a region can also take some models offline.If you’re looking for a capable ChatGPT alternative for complex research and multi-step projects, HaloMate is well worth testing.Final ThoughtsThat’s about it. In this post, I used HaloMate to compare AI models, generate an LLM training diagram, summarize a paper, and create a presentation about knowledge distillation.Its main advantage over single-provider chat apps is flexibility. You can choose from several model families while keeping your files, conversations, and specialized assistants in one place.I also appreciate platforms like HaloMate for giving users another option. We should not have to rely entirely on ChatGPT, Claude, or Gemini when different projects require different models, hosting regions, and memory boundaries.What do you think about HaloMate? Would you use a multi-model AI workspace, or do you prefer keeping each AI assistant separate? Share your thoughts in the comments.This story is published on Generative AI. Connect with us on LinkedIn and follow Zeniteq to stay in the loop with the latest AI stories.Subscribe to our newsletter and YouTube channel to stay updated with the latest news and updates on generative AI. Let’s shape the future of AI together!How I Turned a Research Paper Into a Diagram, a Summary, and a Slide Deck With AI was originally published in Generative AI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Source: Generative AI Pub — Published August 19, 2026 at 02:50 UTC — Category: Image AI