Arnav Arora

Kudos to my collaborators @srishtiy.bsky.social (who co-led this work), @mariaa.bsky.social @serge.belongie.com @iaugenstein.bsky.social for making this happen!

Happy to share that our work on multi-modal framing analysis of news was accepted to #EMNLP2025!

Understanding news output and embedded biases is especially important in today's environment and it's imperative to take a holistic look at it.

Looking forward to presenting it in Suzhou!

Turns out, a good way to reduce bias in LLMs is actually to make them more biased first.
We came up with a neat way to do that using token based fine-tuning and then steering, getting some interesting results for both real world and fictional biases.
Any feedback is welcome!

📢First Workshop on NLP4Democracy @ COLM 2025

📄Submit your non-archival abstracts by June 19
📅Attend the workshop in Montréal on Oct 10 for talks on:
• Applying NLP to study democracy
• Using LLM to improve democratic systems
• AI-driven threats to democracy

#NLP #Democracy #COLM2025 #AIforGood

Greta Thunberg, after trying to do the humanitarian work our governments are supposed to be doing: "Whatever the odds are, we have to keep trying…when you look at the state of the world, everything feels meaningless — but unless you try to do everything you can, that's when we lose our hope, no?"

Join us in Copenhagen for the Pre-ACL 2025 Workshop! 🇩🇰

We’re excited to welcome researchers and practitioners in Natural Language Processing, Generative AI, and Language Technology to a one-day workshop on 26 July 2025 – just ahead of ACL 2025 in Vienna.

Learn more: www.aicentre.dk/events/pre-a...

When ChatGPT Broke an Entire Field: An Oral History | Quanta Magazine Researchers in “natural language processing” tried to tame human language. Then came the transformer.

This is a fantastic oral history of the last 10 years of NLP and AI. www.quantamagazine.org/when-chatgpt...

From the changemyview community on Reddit Explore this post and more from the changemyview community

The mods of r/ChangeMyView shared the sub was the subject of a study to test the persuasiveness of LLMs & that they didn't consent. There’s a lot that went wrong, so here’s a 🧵 unpacking it, along with some ideas for how to do research with online communities ethically. tinyurl.com/59tpt988

In "Investigating Human Values in Online Communities", we perform a high-scale study of the unique values expressed by online communities with different perspectives
arxiv.org/abs/2402.14177 #NAACL2025 #NLProc
@nadavb.bsky.social @rnv.bsky.social @frimelle.bsky.social @iaugenstein.bsky.social

C3NLP Workshop #NAACL2025:
@iaugenstein.bsky.social will be presenting on tailoring LLM outputs to cultures, including where implicit cultural personalisation based on names leads to over-simplification arxiv.org/abs/2502.11995
@rnv.bsky.social @frimelle.bsky.social
bsky.app/profile/frim... #NLProc

The CopeNLU group will be giving four paper presentations and one invited talk at #NAACL2025 this week, on topics including explainable AI and cross-cultural #NLProc
Schedule + more details ⤵️
#XAI @apepa.bsky.social @rnv.bsky.social @nadavb.bsky.social @frimelle.bsky.social @iaugenstein.bsky.social

if you are using primarily local models, which ones are you using and for what lately?

Happy to share that I've joined the Apple Machine Learning Research team in Copenhagen as a research intern!

Will continue to build on topics from my PhD, equitably advancing LLM access for all, working with @maartjeterhoeve.bsky.social and Natalie Schluter.

The high effort solution is to use an LLM to make a browser extension which tracks your academic reading and logs every paper you interact with to github, which builds and publishes a webapp to expose the data.

Which, clearly only a crazy weirdo would do.

dmarx.github.io/papers-feed/

This popped up on HN the other day, and it was one of the more fun “classical cryptography” posts I’ve seen in ages. Roughly speaking, someone discovered that AI models like Claude can decode the Caesar cipher, even when the “key” used is enormous. fi-le.net/byzantine/

Using simple, small models with the goal of usability and scalability of the task, we hope social scientists, journalists and researchers use this as a first step in studying multimodal framing and its intended/unintended effects.

More here:

bsky.app/profile/mari...

When we read the news, images can convey different things than text itself.

Unlike other works which look at text, we study this as a “multimodal” framing problem & analyze where text and images communicate different “frames”.

Checkout our paper here: arxiv.org/abs/2503.20960

@aicentre.dk

I'm so grateful to the British Computing Society & Bloomberg for honouring me with the Karen Spärck Jones Award 🙏
I gave the award lecture on LLMs’ Utilisation of Parametric & Contextual Knowledge at #ECIR2025 today (slides: isabelleaugenstein.github.io/slides/2025_...)
www.bcs.org/membership-a...

New study with @iaugenstein.bsky.social’s group analyzing the interplay between photos and text in the news

New work on multimodal framing! 💫

Some fun results: comparisons of the same frame when expressed in images vs texts. When the "crime" frame is expressed in the article text, there are more political words in the text, but when the frame is expressed in the article image, more police words.

Multi-Modal Framing Analysis of News Automated frame analysis of political communication is a popular task in computational social science that is used to study how authors select aspects of a topic to frame its reception. So far, such s...

Find other interesting results in our paper: arxiv.org/abs/2503.20960 or play with the dataset yourself: huggingface.co/datasets/cop...

Work done with my amazing colleagues @aicentre.dk
@srishtiy.bsky.social @mariaa.bsky.social @serge.belongie.com @iaugenstein.bsky.social

Using our method, you can also get issue-specific frames inductively from the article texts. When publishers are compared across the political spectrum, some clear patterns of how the left frames Immigration vs the right.

Across topics, we find substantial differences in framing across the article and the image. These hold across political leanings as well.

We collect a dataset of 500k articles and images from various publishers in the US, across the political spectrum and systematically analyse differences in framing across them.

Editors choose to convey more subtle messaging through images that can evoke a more emotional response. But can this be measured? We demonstrate a methodology using large language and vision models to do such multi-modal analysis reliably & at scale. We use both generic and issue-specific frames!

🚨New pre-print 🚨

News articles often convey different things in text vs. image. Recent work in computational framing analysis has analysed the article text but the corresponding images in those articles have been overlooked.
We propose multi-modal framing analysis of news: arxiv.org/abs/2503.20960

I have sort of given up on proactively updating the Danish Machine Learning Peoples starter pack. If anyone thinks that they should be added or know someone who should, please don't hesitate to comment here or sent a message 🤗.

bsky.app/starter-pack...

I am still in need of emergency reviewers for ARR this cycle for the computational social science track, please DM me if you have capacity 🙏

Shifting Perspectives: Steering Vector Ensembles for Robust Bias Mitigation in LLMs We present a novel approach to bias mitigation in large language models (LLMs) by applying steering vectors to modify model activations in forward passes. We employ Bayesian optimization to systematic...

NEW PAPER 📜

Shifting Perspectives: Steering Vector Ensembles for Robust Bias Mitigation in LLMs

ArXiv: arxiv.org/abs/2503.05371
GitHub: github.com/groovychoons...
Extremely Unofficial Blog Post: zarasiddique.com/blog/shiftin...

We had the pleasure of hosting @rnv.bsky.social for a talk on "NLP and CSS: lessons from one for the other". Thank you for your great talk!