Evangelos Kazakos

Why they matter

Directory member with public evidence across Agents & robotics, AI business, AI research.

AI signals
60
past 30d
Sources
34
distinct domains
Discussões
17
past 30d
Latest signal
4h ago
View every signal from Evangelos Kazakos →
Postdoctoral researcher @ CIIRC, CTU, Prague working in vision & language. Also robotics noob. PhD from University of Bristol. Ex. Samsung Research (SAIC-C). I love coffee and plants. And socks. 𖤓꩜𓆉𓃰𖤐 https://ekazakos.github.io/

Articles & links

Evangelos Kazakos reposted
Cameron @cameron.stream

Happy Claude Day www.anthropic.com/news/claude...

Introducing Claude Opus 5 anthropic.com
AI Weekly's analysis
  • Anthropic launched Claude Opus 5 on July 24, 2026 at $5 per million input tokens, matching Opus 4.8's rate.
  • On Frontier-Bench v0.1 Opus 5 scored 43.3%, versus 18.7% for Opus 4.8 and 33.7% for Fable 5.
  • Opus 5 becomes the default on Claude Max but sits behind Mythos 5 on cybersecurity tasks, per Anthropic.
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Evangelos Kazakos reposted
Margaret Mitchell @mmitchell.bsky.social

📣 Announcing the release of the 🕊️ Annotated Encyclical 🕊️ from the ethics & society folks at @hf.co. Includes citations to relevant academic work. Very much a WIP. Please add work we haven't added yet! huggingface.co/spaces/socie...

The Annotated Encyclical - a Hugging Face Space by society-ethics huggingface.co
AI Weekly's analysis
  • Hugging Face's society-ethics team added 105 scholarly AI ethics citations to Pope Leo XIV's May 2026 encyclical Magnifica Humanitas.
  • The encyclical declares technology 'is never neutral' and warns that 'never has humanity had such power over itself.'
  • The annotation project is open for community contributions linking academic AI ethics research to the papal document.
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Evangelos Kazakos reposted
adinayakup.bsky.social @adinayakup.bsky.social

BAAI just released the Orca paper 🔥 ( weights coming soon ) huggingface.co/papers/2606.... A Multimodal Latent World Model: it learns the world itself first, and text/images/actions are just different ways to read it out 💡

Paper page - Orca: The World is in Your Mind huggingface.co
AI Weekly's analysis
  • Orca pretrains on 125K hours of video and 160M event annotations using a single Next-State-Prediction objective on a frozen Qwen3.5 backbone.
  • Orca-4B averages 51.8 across MVBench, TemporalBench, 3DSRBench, and SWITCH, ahead of Qwen3.5-4B's 46.7 at the same size.
  • On a real-robot out-of-distribution test Orca reports 36.6% versus π₀.5's 27.6%, despite using no action labels in pre-training.
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Evangelos Kazakos reposted
Gus @gusthema.bsky.social

👁️ Vision Options: Want to make Gemma see even better? The default vision bucket is 280 for token efficiency. To capture maximum detail (like sharp OCR and 2.51MP resolution), manually bump max_soft_tokens to 1120! Try our new interactive Space to see how it works: huggingface…

Gemma 4 - Vision Token Budget - a Hugging Face Space by google huggingface.co
AI Weekly's analysis
  • The Space lets users toggle Gemma 4's per-image budget across five preset sizes: 70, 140, 280, 560, and 1120 tokens.
  • Gemma 4 launched April 2, 2026 under Apache 2.0 across E2B, E4B, 12B Unified, 26B A4B MoE, and 31B dense sizes.
  • The 31B model reportedly hits 76.9% on MMMU Pro and 85.6% on MATH-Vision, with native JSON bounding box output.
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Evangelos Kazakos reposted
@si-cv-graphics.bsky.social

𝟯𝗗-𝗔𝘄𝗮𝗿𝗲 𝗩𝗟𝗠𝘀 𝘄𝗶𝘁𝗵 𝗜𝗺𝗽𝗹𝗶𝗰𝗶𝘁 𝗮𝗻𝗱 𝗘𝘅𝗽𝗹𝗶𝗰𝗶𝘁 𝗚𝗲𝗼𝗺𝗲𝘁𝗿𝗶𝗲𝘀 Wenhao Li, Xueying Jiang, Quanhao Qian ... Gongjie Zhang arxiv.org/abs/2607.21595 Trending on scholar-inbox.com

3D-Aware VLMs with Implicit and Explicit Geometries arxiv.org
AI Weekly's analysis
  • VLM-IE3D adds Implicit and Explicit Geometry Tokens to a VLM, learning 3D structure from RGB video with no depth sensor required.
  • A 3D-aware adapter fuses geometric tokens with 2D visual cues, targeting 3D video detection, visual grounding, dense captioning, and spatial reasoning.
  • The paper was accepted at ECCV 2026, and the authors say code and models are being open-sourced.
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Evangelos Kazakos reposted
@jlake9.bsky.social

1/ DeepSearch-World + DeepSearch-Evolve: a 9B self-evolving web agent for long-horizon search, with verified self-improvement plus released code/data. https://x.com/LiangZhenwen/status/2079710767885279513 https://arxiv.org/abs/2607.07820

DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment arxiv.org
AI Weekly's analysis
  • A 9B-parameter web agent reaches 31.2% on BrowseComp, 61.5% on GAIA, and 93.4% on HotpotQA using self-distillation.
  • The DeepSearch-World environment supplies 420,000 multi-hop QA tasks built from entity-level random walks with reproducible search and page-reading.
  • The training loop cycles through trajectory generation, filtering, data mixing, and fine-tuning without relying on a larger teacher model.
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Recent commentary

I watch the discussion over Anthropic on Bluesky with 🍿🍿🍿

View on Bluesky · ♥ 5 ↻ 0 ↩ 0 · 53d ago

Suddenly everyone's algorithms started "self-improving"... Like, there are no human researchers working in the companies, or thousands of raters for RLHF. LIARS

View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 42d ago

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