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Wisdom of Instruction-Tuned Language Model Crowds. Exploring Model Label Variation

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MilaNLP Lab @milanlp.bsky.social · 6d

#TBT #NLProc Explore 'Wisdom of Instruction-Tuned LLM Crowds' by Plaza et al. LLM labels outperform single models in tasks & languages. But few-shot can't top zero-shot. Supervised models rule.

Flor Miriam Plaza-del-Arco, Debora Nozza, Dirk Hovy. Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024. 2024.

Universal Joy A Data Set and Results for Classifying Emotions Across Languages

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Reposted by MilaNLP Lab

Tanise Ceron @taniseceron.bsky.social · 9d

📣 New Preprint!
Have you ever wondered what the political content in LLM's training data is? What are the political opinions expressed? What is the proportion of left- vs right-leaning documents in the pre- and post-training data? Do they correlate with the political biases reflected in models?

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MilaNLP Lab @milanlp.bsky.social · 9d

#MemoryModay #NLProc 'Universal Joy: A Data Set and Results for Classifying Emotions Across Languages' by Lamprinidis et al. (2021) explores how AI research affects our planet. Tech can be green too! #SustainableTech

Sotiris Lamprinidis, Federico Bianchi, Daniel Hardt, Dirk Hovy. Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. 2021.

MilaNLP Lab @milanlp.bsky.social · 10d

📖For our last Reading Group @donyarn.bsky.social presented
"Culture is Everywhere: A Call for Intentionally Cultural Evaluation" by Oh et al.

Paper: arxiv.org/pdf/2509.01301

#NLProc

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MilaNLP Lab @milanlp.bsky.social · 13d

MilaNLPers at CLiC-it 2025 presenting "Probing Feminist Representations: A Study of Bias in LLMs and Word Embeddings"

Check the paper at clic2025.unica.it/wp-content/u...

#NLProc #clicit25

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MilaNLP Lab @milanlp.bsky.social · 13d

#TBT #NLProc 'Classist Tools: Social Class Correlates with Performance in NLP' by Curry et al. (2024) explores AI's hidden energy problem, and how machine learning impacts environmental sustainability. Tech can be green! #CleanTech

arxiv.org

Benchmarking Post-Hoc Interpretability Approaches for Transformer-based Misogyny Detection

MilaNLP Lab @milanlp.bsky.social · 14d

What makes LLMs agree even when they shouldn’t? 🤔
At our last seminar’s lab, Jan Batzner presented The Brief History of LLM Sycophancy as We Know It.

#NLProc #sycophancy #LLM

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MilaNLP Lab @milanlp.bsky.social · 16d

#MemoryModay #NLProc 'Benchmarking Post-Hoc Interpretability Approaches for Transformer-based Misogyny Detection' - Attanasio et al. Explores reliability of interpretability in hate speech detection.

Giuseppe Attanasio, Debora Nozza, Eliana Pastor, Dirk Hovy. Proceedings of NLP Power! The First Workshop on Efficient Benchmarking in NLP. 2022.

Geolocation with Attention-Based Multitask Learning Models

MilaNLP Lab @milanlp.bsky.social · 20d

#TBT #NLProc 'Geolocation with Attention-Based Multitask Learning Models' by Tommaso Fornaciari, @dirkhovy.bsky.social (2019) reveals how online political talks can become one-sided. Breaking out of our bubbles! #SocialMedia

Tommaso Fornaciari, Dirk Hovy. Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019). 2019.

Dense Node Representation for Geolocation

MilaNLP Lab @milanlp.bsky.social · 21d

📖For this Thursday's Reading Group @elisabassignana.bsky.social presented "The sociolinguistic foundations of language modeling" by Grieve et al.

Paper: www.frontiersin.org/journals/art...

#NLProc #LLM #sociolinguistics

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MilaNLP Lab @milanlp.bsky.social · 23d

#MemoryModay #NLProc 'Dense Node Representation for Geolocation' by Fornaciari & @dirkhovy.bsky.social reveals efficient geolocation methods using node2vec & doc2vec models. Greater network size, less parameters. /publication/2019_m2v/2019_m2v

Tommaso Fornaciari, Dirk Hovy. Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019). 2019.

MilaNLP Lab @milanlp.bsky.social · 26d

🎓We're back with Fridays' lab seminars! Today we had
Suyash Fulay presenting "Truth, Political Bias, and AI Representation".

#NLProc

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MilaNLP Lab @milanlp.bsky.social · 27d

#TBT #NLProc 'MilaNLP @ WASSA: Does BERT Feel Sad When You Cry?' by Fornaciari et al. (2021) indicates that emotion and empathy are not related tasks for prediction.

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MilaNLP Lab @milanlp.bsky.social · 28d

📖For this Thursday's Reading Group @deboranozza.bsky.social
presented two papers on #sycophancy in #LLMs.

Papers: arxiv.org/pdf/2505.13995, arxiv.org/pdf/2310.13548

#NLProc

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MilaNLP Lab @milanlp.bsky.social · Sep 8

#MemoryModay #NLProc 'My Answer is C' by Wang et al. (2024) underscores the scrutiny needed for full text responses in LLMs multi-choice evaluations.

MilaNLP Lab @milanlp.bsky.social · Sep 4

#TBT #NLProc 'Temporal and Second Language Influence on Intra-Annotator Agreement and Stability in Hate Speech Labelling' Abercrombie, @dirkhovy.bsky.social, & Prabhakaran (2023). NLP models: inclusive or not?

MilaNLP Lab @milanlp.bsky.social · Sep 4

We're back with the reading group! 🚀
Today @paul-rottger.bsky.social presented The Levers of Political Persuasion with Conversational AI by Hackenburg et al. (2025)

Paper: arxiv.org/pdf/2507.13919

#NLProc

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MilaNLP Lab @milanlp.bsky.social · Sep 1

#MemoryModay #NLProc Hung et al.'s 2023 paper, 'Can Demographic Factors Improve Text Classification?' finds demographic adaptations of Transformer NLP models don't notably boost performance.

MilaNLP Lab @milanlp.bsky.social · Aug 28

#TBT #NLProc Outstanding Paper at ACL 2024! 'Towards More Meaningful Evaluations for Values and Opinions in Large Language Models' by @paul-rottger.bsky.social et al. Enhancing political bias evaluation.

MilaNLP Lab @milanlp.bsky.social · Aug 25

#MemoryModay #NLProc 'Detecting Misogynous Memes with Text & Image Modalities' by Attanasio, @deboranozza.bsky.social, Bianchi. Their novel system uses Perceiver IO, surpassing all previous benchmarks.

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MilaNLP Lab @milanlp.bsky.social · Aug 21

#TBT #NLProc 'XLM-EMO: Multilingual Emotion Prediction in Social Media Text' by Bianchi, @deboranozza.bsky.social, @dirkhovy.bsky.social (2022) advances cross-language emotion detection, especially for low-resource languages.

MilaNLP Lab @milanlp.bsky.social · Aug 18

#MemoryModay #NLProc Plaza-del-Arco, @debora_nozza, @dirkhovy.bsky.social's 2024 paper "Wisdom Instruction-Tuned Language Model Crowds" shows that multiple LLMs can be BETTER than a single model & specialize across tasks & languages.