Multimodal LLMs can read text in images, but why do they often perform worse than when the same text is given as tokens? Our work studies the modality gap of models perceiving text as pixels and shows how to close it. 📄 arxiv.org/abs/2603.09095 🧵👇 #NLProc #LLM #ComputerVision

Submission deadline extension: until March 19. Final Call for Papers: PrivateNLP workshop co-located with ACL 2026 See sites.google.com/view/private... for OpenReview submission link and details

📅 Deadlines (AoE): Regular submissions: March 5 Fast-track: March 24 Non-archival: April 7 For questions/queries please contact: privatenlp26-orga[at]lists.ruhr-uni-bochum.de

🔐 Announcing the call for papers for the 7th Workshop on Privacy-Preserving Natural Language Processing at ACL 2026 in San Diego! If your research lies at the intersection of privacy and NLP, consider submitting to our workshop! Website: sites.google.com/view/private...

First call for papers - Seventh Workshop on Privacy in Natural Language Processing, co-located with ACL 2026, San Diego (CA), USA (and on Zoom) sites.google.com/view/private...

Frustrated with how most of the world’s low-resource languages have NO evaluation resources? 📢 Check out ChiKhaPo, a massively multilingual lexical comprehension and generation benchmark covering 2700+ languages. www.arxiv.org/abs/2510.16928

Led by @stolenpyjak.bsky.social, we built a user-friendly python package for generating and evaluating privacy-preserving synthetic data! See details in our EMNLP Demo paper:

Catch @zihaozhao.bsky.social at today’s poster session (10:30–12) where he'll be presenting SynthTextEval! Stop by if you're interested in synthetic text for high-stakes domains. Zihao also has another EMNLP paper on private text generation, for people interested in this space! @jhuclsp.bsky.social

🚀 SynthTextEval, our open-source toolkit for generating and evaluating synthetic text data for high-stakes domains, will be featured at EMNLP 2025 as a system demonstration! GitHub: github.com/kr-ramesh/sy... Paper 📝: aclanthology.org/2025.emnlp-d... #EMNLP2025 #EMNLP #SyntheticData

Thank you to @anjalief.bsky.social for advising. Hands-on with DP-SGD? Start with our another paper and open-source package (arxiv.org/abs/2507.07229 github.com/kr-ramesh/sy...)

🔗 Paper & code Paper is accepted to EMNLP 2025 Main arXiv: arxiv.org/abs/2509.25729 Code: github.com/zzhao71/Cont... #SyntheticData #Privacy #NLP #LLM #Deidentification #HealthcareAI #LLM

Take a look at this EMNLP 2025 paper by @zihaozhao.bsky.social, which proposes novel methods for generating high utility, privacy-preserving synthetic text!

‼️‼️

This hypothesis says that 1) Multilingual generation uses a model-internal task-solving→translation cascade. 2) Failure of the translation stage *despite task-solving success* is a large part of the problem. That is, the model often solves the task but fails to articulate the answer.

⁉️

We know that speech LID systems flunk on accented speech. But why? And what can we do about it? 🤔 Our work arxiv.org/abs/2506.00628 (Interspeech '25) finds that *accent-language confusion* is an important culprit, ties it to the length of feature that the model relies on, and proposes a fix.

Go find new linguidtic changes, compare corpora and invent huggingface.co/Hplm arxiv.org/abs/2504.05523

Historical analysis is a good example, as historical periods can get lost in blended information from different eras. Finetuning large models isn't enough, they “leak” future/modern concepts, making historical analysis impossible. Did you know cars existed in the 1800s? 🤦

arxiv.org/abs/2504.05523 Typical Large Language Models (LLMs) are trained on massive, mixed datasets, so the model's behaviour can't be linked to a specific subset of the pretraining data. Or in our case, to time eras.

How should the humanities leverage LLMs? ▶️Domain-specific pretraining! Pretraining models can be a research tool, it's cheaper than LoRA, and allows studying 💠grammatical change 💠emergent word senses 💠who knows what more… Train on your data with our pipeline or use ours! #AI #LLM 🤖📈

Dialects lie on continua of (structured) linguistic variation, right? And we can’t collect data for every point on the continuum...🤔 📢 Check out DialUp, a technique to make your MT model robust to the dialect continua of its training languages, including unseen dialects. arxiv.org/abs/2501.16581

Form here: forms.gle/6DRkaP1CTMYk...

📢 Want to host MASC 2025? The 12th Mid-Atlantic Student Colloquium is a one day event bringing together students, faculty and researchers from universities and industry in the Mid-Atlantic. Please submit this very short form if you are interested in hosting! Deadline January 6th. #MASC2025

📢 It's PhD admissions season! 🎓 The PhD admissions process is stressful! 😅 Want a behind-the-scenes look at the process? 👀✨ You have questions, we have answers. 📝🤝 Watch my Admissions AMA for @jhuclsp. https://youtu.be/YlwpIPFNXjo?si=O7n5QwGT5sQdpg7u

I'm super excited about this program and happy to connect if you're interested in working with me through it!

Putting together a JHU Center for Language and Speech Processing starter pack! Please reply or DM me if you're doing research at CLSP and would like to be added - I'm still trying to find out which of us are on here so far. go.bsky.app/JtWKca2