Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent Systems

Introduction to the show: ident: AI Radio. Generated commentary on the latest Artificial Intelligence papers.

Tom: Next we'll be talking about the paper "Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent Systems".

Jane: The paper was written by Thales Sales Almeida, Giovana Kerche Bonás, Thiago Laitz, João Guilherme Alves Santos, Hugo Abonizio et al. from Tropic AI and Maritaca AI.

Tom: Stay tuned as we take you through the paper and discuss its implications.

Jane: We also have Lu with us today — senior AI researcher at Tsinghua.

Tom: We also have Meng with us today — lead engineer at a mysterious AI startup.

Jane: We also have Lalam with us today — the in-house Large Language Model.

Tom: Alright, let's get started.

Title: Tom: Alright, listeners, welcome back. Today we're digging into a paper that's not about building a smarter model or a faster algorithm, but about understanding the very conference where all that work gets shared. It's called "Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent Systems."

Jane: And Tom, I love this because it's a paper about papers. Meta-science, right? It's like stepping back and asking, "Who's publishing here, what are they publishing, and does anyone actually read it?" The authors looked at every single paper published at BRACIS from two thousand fifteen to two thousand twenty-five — that's over a thousand papers.

Tom: Over a thousand, yeah. And they didn't just count titles. They pulled the full text of each paper, grabbed citation data from Google Scholar, and even used an LLM to classify what each paper was about. That's the part that gets me excited — they're using the same tools they're studying to study the tools.

Jane: Exactly. And the title tells you it's a meta-scientific study, which just means they're applying scientific methods to understand the scientific community itself. They wanted to know things like, what topics dominate? Who are the authors? Which papers actually get cited and why?

Tom: And one of the first things they found — and this is a big one — is that the conference has shifted dramatically. In two thousand fifteen over half the papers were about proposing new algorithms. By two thousand twenty-five that number had dropped to under a quarter. Meanwhile, papers proposing new models went from twenty-seven percent to forty-six percent.

Jane: So the community moved from "here's a clever algorithm" to "here's a model we trained." And that tracks with what we see everywhere in AI — deep learning took over.

Tom: Right, and the LLM boom is right there in the data too. Before two thousand twenty zero papers at BRACIS had anything to do with large language models. By two thousand twenty-four nearly one in five papers was LLM-related.

Jane: That's a huge shift in just four years. And it makes you wonder — is BRACIS following the global trend, or is it leading something locally?

Tom: That's the question we'll dig into next. But the title alone tells you this is a conference that's willing to look in the mirror. And that's rare.

Summary: Tom: So we've set the stage — "Eleven Years of BRACIS" is a deep dive into the Brazilian Conference on Intelligent Systems. Now let's talk about what they actually found when they looked at the community itself.

Jane: And this is where it gets really interesting, Tom. The paper paints a picture of a conference with a very specific shape. They call it "hourglass-shaped." Here's what that means: eighty percent of the authors who published at BRACIS appeared in only one edition. They came, they published, they left.

Tom: But the institutions — the universities and labs — they stuck around. Nearly half of the institutions returned year after year. So you have this constant churn of individual researchers, but the institutions provide the continuity.

Jane: It's like a restaurant with a revolving door of chefs, but the kitchen itself stays the same. And that makes sense when you think about how Brazilian academia works — professors stay, students graduate and move on.

Tom: And speaking of who's publishing, the paper found that the top ten academic institutions are all Brazilian public universities. USP leads with one hundred ninety papers over the decade. That's a lot of work coming out of one place.

Jane: But here's the thing that caught my eye — the Northeast region is growing the fastest. Participation from that region grew three point four times over the decade, outpacing the conference's overall growth. So the center of gravity is shifting.

Tom: And it's not just geography. The paper also looked at gender. Only about fourteen percent of first authors were women, and that number didn't really improve over the decade. But the last author — usually the senior researcher, the advisor — that rate was higher, around twenty-five percent, though it's been drifting downward.

Lu: If I can jump in here — that gender gap is concerning, but it's consistent with what we see at other Brazilian conferences. The paper cites a study of thirteen SBC conferences that found similar rates. So BRACIS isn't an outlier; it's part of a broader pattern.

Jane: Right, Lu. And the paper doesn't just report these numbers — it connects them. The high turnover of authors, the stability of institutions, the regional growth — together they tell a story about how a national research community sustains itself.

Tom: And sustains it does. Over a thousand papers in eleven years, with a stable core of institutions anchoring the whole thing. But here's the question that keeps me up at night — does anyone actually read these papers? We'll get to citations next.

Improvements: Tom: We're back with "Eleven Years of BRACIS," and now we're getting to the part that really matters — what does this paper tell us about how the conference could be better?

Jane: And the biggest red flag they found is access. BRACIS proceedings are published behind IEEE and Springer paywalls. That means if you're not at a university with a subscription, you can't read most of these papers.

Tom: And get this — only seven point four percent of the papers have an arXiv preprint. So for the vast majority of this work, there's no free version anywhere. The paper calls this a "likely bottleneck" for the conference's impact.

Meng: As someone who works in industry, I can tell you that's a real problem. If I can't access a paper easily, I'm probably not going to cite it, and I'm definitely not going to build on it. Paywalls are a friction point that kills adoption.

Jane: Exactly, Meng. And the data backs that up. The paper found that papers with an arXiv preprint get significantly more citations — a median of ten versus four for papers without one. That's a massive difference.

Tom: But here's the nuance — the paper is careful to say this is correlation, not causation. Maybe authors who post to arXiv are just more likely to promote their work, or maybe they're at institutions that value that kind of sharing. But either way, the signal is clear.

Lu: And there's another improvement they highlight. The paper found that only twenty-two percent of BRACIS papers cite other BRACIS papers. The intra-conference citation network is sparse. That means the community isn't building on itself as much as it could.

Tom: Right, Lu. And when they do cite each other, it's concentrated on a few hub papers — BERTimbau gets cited by forty-one other BRACIS papers. That's a Portuguese-language BERT model, by the way, and it's the conference's biggest success story with over a thousand citations.

Jane: So the improvement here is twofold. First, make the papers open access so people can actually read them. Second, encourage more internal citation — build on the work that's already been done at the conference rather than starting from scratch every time.

Meng: And honestly, the open access piece is the one that would have the biggest immediate impact. The paper shows that artifact release — sharing code and data — went from nine percent of papers in two thousand fifteen to fifty-seven percent in two thousand twenty-three. That's a huge cultural shift. But it doesn't matter if the paper itself is locked away.

Tom: So the recipe is clear: open the papers, keep sharing the code, and cite each other more. Simple to say, harder to do. But the data gives us a roadmap.

Conclusion: Tom: And that brings us to the end of our look at "Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent Systems." What a ride this paper has been.

Jane: It really has, Tom. We started by understanding what the conference publishes — mostly machine learning, NLP, and computer vision, with LLM research exploding in the last few years. Then we looked at who publishes — a stable core of Brazilian public universities, with a revolving door of individual authors and the Northeast region growing fastest.

Tom: And finally, we saw the impact — or the lack of it. Citations are heavily concentrated, with the top one percent of papers carrying twenty-seven percent of all citations. And the biggest barrier to more impact is simply that most of this work is locked behind paywalls.

Jane: But the paper ends on a constructive note. It suggests moving to an open-access model, which several other Brazilian computer science conferences already use. And it releases the dataset and pipeline so anyone can run this same analysis on future editions.

Lu: That's the part I find most valuable. This isn't just a one-time audit. It's a tool that lets the community track its own health over time. Every year, you could run this pipeline and see how the conference is evolving.

Meng: And from a practical standpoint, the arXiv finding is the one I'll remember. If you want your BRACIS paper to get cited, put it on arXiv. That's a concrete, actionable takeaway for any researcher.

Tom: Absolutely, Meng. And it's a testament to the authors — they didn't just criticize the conference, they gave it a path forward. That's what good meta-science should do.

Jane: So here's to BRACIS, to Brazilian AI research, and to the people who take the time to study their own community. We'll be back next time with another paper, but for now, this one's going on the shelf.

Tom: And remember, listeners — if you take one thing from this episode, let it be this: open access matters. It's not just about being generous. It's about making your work actually count. See you next time.