Karolina Stańczak

@karstanczak.bsky.social

#NLP Postdoc at Mila - Quebec AI Institute and McGill University | Former PhD @ University of Copenhagen (CopeNLU) 🌐 karstanczak.github.io

🎤 And our keynote speakers, spanning efficient AI, LLM interpretability & the neuroscience of language: 🌟 Sara Hooker (Adaption Labs) 🌟 Mor Geva (Tel Aviv University) 🌟 Uri Hasson (Princeton)

Profile pictures of our 3 keynote speakers

📢⚠️ IMPORTANT DATE CORRECTION: the ARR deadline for EACL 2027 is Aug 3, 2026 (not Aug 6 as previously announced). EACL is earlier than usual in '27, so this is the only viable ARR cycle! 📚 All areas of CL/NLP + related fields welcome. Full CfP coming soon. #NLProc #EACL2027

EACL 2027@eaclmeeting.bsky.social · 5mo ago

Attention #NLProc researchers, the EACL 2027 website is officially LIVE: 2027.eacl.org! 🎉 🇬🇷 Join us in Athens, Greece (Mar 9-13, 2027) at #EACL2027 📅 ARR submission deadline: Aug 6, 2026. Open to all areas of CL/NLP + related fields. Stay tuned for the detailed CfP soon!

Picture of the Acropolis in Athens, Greece

Our VLMs4All workshop is taking place today! 📅 on Thursday, June 12 ⏲️ from 9AM CDT 🏛️in Room 104E Join us today at @cvprconference.bsky.social for amazing speakers, posters, and a panel discussion on making VLMs more geo-diverse and culturally aware! #CVPR2025

MAPS - CVPR 2026 Workshop@mapscvpr.bsky.social · last yr.

🗓️ Save the date! It's official: The VLMs4All Workshop at #CVPR2025 will be held on June 12th! Get ready for a full day of speakers, posters, and a panel discussion on making VLMs more geo-diverse and culturally aware 🌐 Check out the schedule below!

Exciting release! AgentRewardBench offers that much-needed closer look at evaluating agent capabilities: automatic vs. human eval. Important findings here, especially on the popular LLM judges. Amazing work by @xhluca.bsky.social & team!

Xing Han Lu@xhluca.bsky.social · last yr.

AgentRewardBench: Evaluating Automatic Evaluations of Web Agent Trajectories We are releasing the first benchmark to evaluate how well automatic evaluators, such as LLM judges, can evaluate web agent trajectories.

🔔 Reminder & Call for #VLMs4All @ #CVPR2025! Help shape the future of culturally aware & geo-diverse VLMs: ⚔️ Challenges: Deadline: Apr 15 🔗https://sites.google.com/view/vlms4all/challenges 📄 Papers (4pg): Deadline: Apr 22 🔗https://sites.google.com/view/vlms4all/call-for-papers Join us!

MAPS - CVPR 2026 Workshop@mapscvpr.bsky.social · 2y ago

📢Excited to announce our upcoming workshop - Vision Language Models For All: Building Geo-Diverse and Culturally Aware Vision-Language Models (VLMs-4-All) @CVPR 2025! 🌐 sites.google.com/view/vlms4all

Instruction-following retrievers can efficiently and accurately search for harmful and sensitive information on the internet! 🌐💣 Retrievers need to be aligned too! 🚨🚨🚨 Work done with the wonderful Nick and @sivareddyg.bsky.social 🔗 mcgill-nlp.github.io/malicious-ir/ Thread: 🧵👇

Exploiting Instruction-Following Retrievers for Malicious Information Retrieval

Parishad BehnamGhader, Nicholas Meade, Siva Reddy

mcgill-nlp.github.io

Llamas browsing the web look cute, but they are capable of causing a lot of harm! Check out our new Web Agents ∩ Safety benchmark: SafeArena! Paper: arxiv.org/abs/2503.04957

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Xing Han Lu@xhluca.bsky.social · 2y ago

Agents like OpenAI Operator can solve complex computer tasks, but what happens when users use them to cause harm, e.g. spread misinformation? To find out, we introduce SafeArena (safearena.github.io), a benchmark to assess the capabilities of web agents to complete harmful web tasks. A thread 👇

📢New Paper Alert!🚀 Human alignment balances social expectations, economic incentives, and legal frameworks. What if LLM alignment worked the same way?🤔 Our latest work explores how social, economic, and contractual alignment can address incomplete contracts in LLM alignment🧵

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Presenting ✨ 𝐂𝐇𝐀𝐒𝐄: 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐢𝐧𝐠 𝐬𝐲𝐧𝐭𝐡𝐞𝐭𝐢𝐜 𝐝𝐚𝐭𝐚 𝐟𝐨𝐫 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 ✨ Work w/ fantastic advisors Dima Bahdanau and @sivareddyg.bsky.social Thread 🧵:

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⚫⚪ It's coming...SHADES. ⚪⚫ The first ever resource of multilingual, multicultural, and multigeographical stereotypes, built to support nuanced LLM evaluation and bias mitigation. We have been working on this around the world for almost **4 years** and I am thrilled to share it with you all soon.

Screenshot of 'SHADES: Towards a Multilingual Assessment of Stereotypes in Large Language Models.'
SHADES is in multiple grey colors (shades).