
Guatemalan 🇬🇹 physicist, Postdoc @CVC_UAB, researching autonomous driving.
Barcelona
Joined October 2011
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- Following367
- Followers1.1K
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Diego Porres retweeted
Ok my turn to be brave for the good of the community
Not sure who needs to hear it, but usually models with JEPA in their title are bad. Like LeJepa is much worse than DINO in practice
Pretty papers, fancy math, bad results
V-JEPA 2.1 is probably the only exception [1/2]
Can we please have more posts like this one?
Too many people are afraid to openly criticize posts and papers, and that really hurts the community and lets bad ideas spread fast
Thank you @giffmana for saving me (and thousands other people) an hour of my time
Claude struggled to write my kind of music (theory-heavy music for nerds lol) until Opus 5.5. I asked for a motif passed from one player to the next and reinterpreted, with a solo from each instrument demonstrating specific techniques, and it made this piece, Ouroboros. Then I had it animate the video using tools I've built over the past year while reverse-engineering music to study theory.
Diego Porres retweeted
These are all SVG!
Something really cool is coming to @QuiverAI around icons, asset families, and styles.
Reply for early access.
Diego Porres retweeted
🪗 Your Transformer Is Secretly Elastic 🧵👇
Transformer families come in a few fixed sizes, so you commit to one for your hardware and latency constraints, even as query loads vary. What if a single pre-trained model could serve every budget?
We learn one importance ranking over every MLP neuron and attention head, once, with frozen weights. At inference time, the model can then be pruned to any computational budget by dropping its least important units, without retraining.
Across 27 vision and text encoders spanning 22M to 8B parameters, performance degrades smoothly up to 60% sparsity. For example, pruning DINOv3 ViT-H+/16 to 50% sparsity removes 427M parameters, for only a 0.8% drop in ImageNet-1k linear probing.
Super fun project in collaboration with Dheeraj Varghese (@dhevarghese), supervised by Gertjan J. Burghouts (@gjburghouts) and Cees Snoek (@cgmsnoek)
🌐 Project page: secretly-elastic.ashita.nl
Diego Porres retweeted
Word on the computer vision streets: “publish or perish” has now become “publish, promote, or perish”
Diego Porres retweeted
Teaching image generation models about hex codes. Did not realize this was a problem till today. #ECCV2026
Diego Porres retweeted
With NumColor you can generate images with precise hex/RGB color control.
Trained only on FLUX, it transfers zero-shot to SD3, SD3.5, PixArt-α and PixArt-Σ — 4–9× better color accuracy, 10–30× better color harmony.
See you at ECCV!
@aatiibutt @j_vazquezcorral @Alvaro_kai93
Diego Porres retweeted
What have I just witnessed @QuiverAI!!? My prompt drawn before my eyes, as an SVG 👏🙇♂️
Prompt and image in 🧵👇
Diego Porres retweeted
New Arrow is coming. Come get an exclusive taste 💫
Creative Coding Night with @cursor_ai, powered by @a16z.
August 25, San Francisco.
We’ve been building something big. And tomorrow, we’re showing it for the first time. Everyone in the room gets exclusive early access – before it goes public.
See you there.
Diego Porres retweeted
📢 Open PhD position in my group at @DTUCompute
🔬 Computer vision, vision-language models
💰 Fully funded, 3 yrs
📍 Copenhagen area 🇩🇰
🗓️ Deadline: 20 September
Do multimodal AI research in one of Europe's best cities.
Apply now: efzu.fa.em2.oraclecloud.com/…
Diego Porres retweeted
Join us on August 25 in SF for a creative coding hackathon powered by the coding and design agents from @Cursor_ai and @QuiverAI.
We’ve got a lot cooking with Arrow. Come get a taste 💫💫
We @a16z are cohosting a ✨ creative coding night ✨ with @QuiverAI and @cursor_ai on 8/25
Bring a laptop, build beautiful, interactive pages, playable widget, animated scenes... and demo it at the end. Free Quiver + Cursor credits, and awards for the top 3 👇
Diego Porres retweeted
Generate SVG stickers with Arrow. Extend your style!
Try it now with the Quiver API
docs.quiver.ai
Diego Porres retweeted
POV: You’re being saved from a wildfire in 2032
Researchers proved every major LLM is secretly obsessed with Japan.
And they finally figured out why.
For years, we’ve been told that AI is entirely Western-centric, that it just reflects Silicon Valley and American values.
A landmark paper by Cardiff and Basque researchers tested 31,680 cultural prompts across 24 languages on frontier models like ChatGPT, Claude, and Gemini.
The results shattered that assumption.
In six out of eight frontier models, Japan was the single most frequently referenced country when asked open-ended cultural questions.
Ask about traditional dances, festivals, or everyday practices in an open context, and the AI defaults to Japan.
Over and over again.
Here is the twist nobody expected.
This bias doesn't come from raw pre-training internet data.
The researchers tracked where the obsession forms. It emerges after pre-training, during the supervised fine-tuning and alignment phase when humans teach the AI how to behave.
Why Japan?
Because decades of global soft power, rich cultural export, and clean, universally admired digital archives make Japanese culture uniquely "safe" for AI safety filters to lean on.
When labs train models to be harmless and universally pleasing, the AI defaults to the cultural equivalent of comfort food.
It avoids controversy by talking about anime, sushi, and tradition.
Diego Porres retweeted
⏱️ 1 day left to apply to the ELLIS Summer School on Autonomous Driving 🚗
Let's meet our amazing speakers!
Today we introduce @ftm_guney
(Professor at Koç University in Istanbul, Türkiye)
📝Deadline: Friday, June 12, 11:59 PM AoE pages.cvc.uab.es/ssadriving/





























