Andrei Muresanu

PhD Student @ UofT. Co-supervised by Nicolas Papernot and Zhijing Jin. Using interpretability to improve model evaluations.

[Ryan Faulkner @_rfaulk]

Excited to share our latest research and open-source codebase: AgentElect! 🚀

We investigate how AI systems can leverage elections to navigate resource-based social dilemmas and drive multi-agent cooperation in common pool resource problems.

📄 Read the paper: https://t.co/4uV0H4FVJ9💻
Explore the code: https://t.co/8USGpc62Yv

#MultiAgentSystems #AI #MachineLearning #AIResearch #OpenSource

[Yongjin Yang @_yongjinny]

For everyone visiting Seoul for #ICML2026, my wife @easyminie_ put together a very practical Korea guide based on 20+ years of living here 🇰🇷

It has a COEX-focused ICML guide, vegan-friendly restaurants, useful apps, cafes, food spots, transport tips, and many curated map lists organized around the conference venue.

Hope it helps people enjoy Seoul during ICML!

https://t.co/heMkSRl6Pg

[Yongjin Yang @_yongjinny]

Multi-domain RLVR trains one model across math, code, logic, science, tables, and simulation. But the key curriculum question is usually fixed or hand-tuned: which domain should we sample next?

🚨 New paper: Transfer-Aware Curriculum (TAC). TAC asks not only “where is the model learning right now?” but also “will this gradient step help the other domains too?”

⚡ The signal is almost free: we reuse GRPO gradients already computed during training, sketch them with random projections, and estimate cross-domain transfer by gradient alignment. No extra rollouts, no held-out probes, <1% wall-clock overhead.

📈 TAC gets the best macro-average accuracy on both Qwen3-1.7B and Llama3.2-3B, with up to +2.8 pts, or 10% relative, over a learnability-only bandit.

😲 Surprise: math was among the least transferable domains, even though RLVR often leans on it most.

[Zhijing Jin @ZhijingJin]

Excited for our "Trustworthy AI for Good" (AI4GOOD) Workshop at #ICML2026! As AI agents increasingly affect our lives, it is key to bridge #ResponsibleAI, social good, and governance. Let’s build solutions together!

⏰ Submission deadline: April 30, 2026 (AoE)
🎙️Confirmed speakers: @Yoshua_Bengio, Joel Z. Leibo (@jzl86), Maksym Andriushchenko (@maksym_andr), @OanaIgnatRo [More to come!]

📍July 10-11, 2026 · Seoul🇰🇷
🔗 https://t.co/2NsL7jFpso

📝 Submit: https://t.co/RcOwxoPRtS
📣 Be a reviewer: https://t.co/8tRAm3onbl

[Rohan Subramani @rohan_subramani]

Just went on my first podcast! Enjoyed discussing continual learning for LLM agents and its safety implications with Anna on The Glitchatorio, you can check it out at either of the below links:

Spotify: https://t.co/2ph4bgtk2e

Apple Podcasts: https://t.co/leyRwUyV9W

[AK @_akhaliq]

Celebrity Mortal Kombat, Midjourney AI + gen2 + ElevenLabs by u/fignewtgingrich

[Jessy Lin @realJessyLin]

How can agents understand the world from diverse language? 🌎

Excited to introduce Dynalang, an agent that learns to understand language by 𝙢𝙖𝙠𝙞𝙣𝙜 𝙥𝙧𝙚𝙙𝙞𝙘𝙩𝙞𝙤𝙣𝙨 𝙖𝙗𝙤𝙪𝙩 𝙩𝙝𝙚 𝙛𝙪𝙩𝙪𝙧𝙚 with a multimodal world model!

[Danijar Hafner @danijarh]

A big day for Python! The steering council has decided to remove the GIL:
- Will unlock fast multithreading
- User code can stay exactly the same
- Experimental support planned for 3.13 (Oct 2024)
https://t.co/XMBca292E3

[Łukasz Langa @llanga]

Wow. @Meta commits to dedicate three engineer-years to implement the removal of the GIL from #Python and fix upcoming compatibility and performance issues with it.

All this dependent on whether the Steering Council accepts PEP 703.

https://t.co/8YqL9KwYL1

[Harris Chan @SirrahChan]

STEVE-1 surprisingly also works with visual prompts taken from real life videos, thanks to using MineCLIP's embedding! See🧵👇

Such a fun project with @Shalev_lif @keirp1 @jimmybajimmyba @SheilaMcIlraith

(Credits to @CorruptCarnage and Soil Television for the source videos)

[Keiran Paster @keirp1]

Meet STEVE-1, an instructable generative model for Minecraft. STEVE-1 follows both text and visual instructions and acts on raw pixel inputs with keyboard and mouse controls. Best of all - it only cost $60 to train!

w/ @Shalev_lif @SirrahChan @jimmybajimmyba @SheilaMcIlraith

[Michael Zhang @michaelrzhang]

Excited to share Boosted Prompt Ensembles! Inspired by boosting algorithms, we propose an algorithm that automatically grows an ensembles of prompts to cover a target problem space.

Led by @silviupitis and with @andrew_wang10 and @jimmybajimmyba

[Andrei Muresanu @_AndreiMuresanu]

In case anyone needs the Alpaca dataset in the flan_v2 format, you can find it here😊: https://t.co/v7l2r8Pc97

[Andrej Karpathy @karpathy]

One of my favorite results in 2022 was that it's not enough to just think step by step. You must also make sure to get the right answer :D
https://t.co/NbwY5brTgs
(actually a nice insight into a psychology of a GPT; it pays to condition on a high reward)

[Andrei Muresanu @_AndreiMuresanu]

@ZhangLunjun Not necessarily. Distilling could simply be a shortcut.

[Vivek Haldar @vivekhaldar]

Latest video looks at a paper by @Yongchao_Zhou_ @_AndreiMuresanu @ziwen_h @silviupitis @SirrahChan @jimmybajimmyba @keirp1 that tries to automate the process of coming up with good prompts for large language models

https://t.co/JANYMAWzbu

[Michael Zhang @michaelrzhang]

Neat result from applying automated prompt generation on translation. Referencing "Google Translate" in the prompt improves the performance of the model.

[Keiran Paster @keirp1]

Another interesting prompt found using APE: rather than ask GPT to translate to Spanish directly, ask it to pretend as if it's using Google Translate for stronger performance!

[Andrei Muresanu @_AndreiMuresanu]

@KabalanFreeman @keirp1 @Yongchao_Zhou_ @ziwen_h @silviupitis @SirrahChan @jimmybajimmyba We define the score of a prompt x as: E[logP(correct_output | input, x)] =~ 1/n * (logP(correct_output_1 | input_1, x) + … + logP(correct_output_n | input_n, x)) where n is the number of examples in the user provided demo. We then say the prompt with the highest score is best.

[Keiran Paster @keirp1]

@Yongchao_Zhou_ made a GUI for APE so that you don't have to write a single line of code to try it out for yourself:

https://t.co/JklwzRM3gk