DaCENA: Serendipitous News Reading with Data Contexts. - Matteo Palmonari; Giorgio Uboldi; Marco Cremaschi; Daniele Ciminieri; Federico Bianchi 001 (ESWC (Satellite Events), 2015)

Joint Learning of Entity and Type Embeddings for Analogical Reasoning with Entities. - Federico Bianchi 001; Matteo Palmonari (NL4AI@AI*IA, 2017)

Actively Learning to Rank Semantic Associations for Personalized Contextual Exploration of Knowledge Graphs. - Federico Bianchi 001; Matteo Palmonari; Marco Cremaschi; Elisabetta Fersini (ESWC (1), 2017)

Type Vector Representations from Text: An Empirical Analysis. - Federico Bianchi 001; Mauricio Soto; Matteo Palmonari; Vincenzo Cutrona (DL4KGS@ESWC, 2018)

Towards Encoding Time in Text-Based Entity Embeddings. - Federico Bianchi 001; Matteo Palmonari; Debora Nozza (ISWC (1), 2018)

Reasoning over RDF Knowledge Bases using Deep Learning. - Monireh Ebrahimi; Md. Kamruzzaman Sarker; Federico Bianchi 001; Ning Xie 009; Derek Doran; Pascal Hitzler (CoRR, 2018)

Training Temporal Word Embeddings with a Compass. - Valerio Di Carlo; Federico Bianchi 001; Matteo Palmonari (AAAI, 2019)

On the Capabilities of Logic Tensor Networks for Deductive Reasoning. - Federico Bianchi 001; Pascal Hitzler (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2019)

Mapping Lexical Knowledge to Distributed Models for Ontology Concept Invention. - Manuel Vimercati; Federico Bianchi 001; Mauricio Soto; Matteo Palmonari (AI*IA, 2019)

Supporting Journalism by Combining Neural Language Generation and Knowledge Graphs. - Marco Cremaschi; Federico Bianchi 001; Andrea Maurino; Andrea Primo Pierotti (CLiC-it, 2019)

Complementing Logical Reasoning with Sub-symbolic Commonsense. - Federico Bianchi 001; Matteo Palmonari; Pascal Hitzler; Luciano Serafini (RuleML+RR, 2019)

Experimental neural network enhanced quantum tomography. - Adriano Macarone Palmieri; Egor Kovlakov; Federico Bianchi 001; Dmitry Yudin; Stanislav Straupe; Jacob D. Biamonte; Sergei Kulik (CoRR, 2019)

On the composition and recommendation of multi-feature paths: a comprehensive approach. - Vincenzo Cutrona; Federico Bianchi 001; Michele Ciavotta; Andrea Maurino (GeoInformatica, 2019)

"You Sound Just Like Your Father" Commercial Machine Translation Systems Include Stylistic Biases. - Dirk Hovy; Federico Bianchi 001; Tommaso Fornaciari (ACL, 2020)

UNIMIB @ DIACR-Ita: Aligning Distributional Embeddings with a Compass for Semantic Change Detection in the Italian Language (short paper). - Federico Belotti; Federico Bianchi 001; Matteo Palmonari (EVALITA, 2020)

The Embeddings That Came in From the Cold: Improving Vectors for New and Rare Products with Content-Based Inference. - Jacopo Tagliabue; Bingqing Yu; Federico Bianchi 001 (RecSys, 2020)

Tough Tables: Carefully Evaluating Entity Linking for Tabular Data. - Vincenzo Cutrona; Federico Bianchi 001; Ernesto Jiménez-Ruiz; Matteo Palmonari (ISWC (2), 2020)

"An Image is Worth a Thousand Features": Scalable Product Representations for In-Session Type-Ahead Personalization. - Bingqing Yu; Jacopo Tagliabue; Ciro Greco; Federico Bianchi 001 (WWW (Companion Volume), 2020)

What the [MASK]? Making Sense of Language-Specific BERT Models. - Debora Nozza; Federico Bianchi 001; Dirk Hovy (CoRR, 2020)

Compass-aligned Distributional Embeddings for Studying Semantic Differences across Corpora. - Federico Bianchi 001; Valerio Di Carlo; Paolo Nicoli; Matteo Palmonari (CoRR, 2020)

Knowledge Graph Embeddings and Explainable AI. - Federico Bianchi 001; Gaetano Rossiello; Luca Costabello; Matteo Palmonari; Pasquale Minervini (CoRR, 2020)

Fantastic Embeddings and How to Align Them: Zero-Shot Inference in a Multi-Shop Scenario. - Federico Bianchi 001; Jacopo Tagliabue; Bingqing Yu; Luca Bigon; Ciro Greco (CoRR, 2020)

BERT Goes Shopping: Comparing Distributional Models for Product Representations. - Federico Bianchi 001; Bingqing Yu; Jacopo Tagliabue (CoRR, 2020)

Neural-symbolic integration and the Semantic Web. - Pascal Hitzler; Federico Bianchi 001; Monireh Ebrahimi; Md. Kamruzzaman Sarker (Semantic Web, 2020)

Corpus-based Comparison of Distributional Models of Language and Knowledge Graphs. - Federico Bianchi 001 (2020)

Knowledge Graph Embeddings and Explainable AI. - Federico Bianchi 001; Gaetano Rossiello; Luca Costabello; Matteo Palmonari; Pasquale Minervini (Knowledge Graphs for eXplainable Artificial Intelligence, 2020)

Tough Tables: Carefully Benchmarking Semantic Table Annotators. - Vincenzo Cutrona; Federico Bianchi 001; Ernesto Jiménez-Ruiz; Matteo Palmonari (Zenodo, 2020)

Tough Tables: Carefully Evaluating Entity Linking for Tabular Data. - Vincenzo Cutrona; Federico Bianchi 001; Ernesto Jiménez-Ruiz; Matteo Palmonari (Zenodo, 2020)

Neuro-Symbolic Deductive Reasoning for Cross-Knowledge Graph Entailment. - Monireh Ebrahimi; Md. Kamruzzaman Sarker; Federico Bianchi 001; Ning Xie 009; Aaron Eberhart; Derek Doran; HyeongSik Kim 001; Pascal Hitzler (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2021)

On the Gap between Adoption and Understanding in NLP. - Federico Bianchi 001; Dirk Hovy (ACL/IJCNLP (Findings), 2021)

Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence. - Federico Bianchi 001; Silvia Terragni; Dirk Hovy (ACL/IJCNLP (2), 2021)

Cross-lingual Contextualized Topic Models with Zero-shot Learning. - Federico Bianchi 001; Silvia Terragni; Dirk Hovy; Debora Nozza; Elisabetta Fersini (EACL, 2021)

BERTective: Language Models and Contextual Information for Deception Detection. - Tommaso Fornaciari; Federico Bianchi 001; Massimo Poesio; Dirk Hovy (EACL, 2021)

SWEAT: Scoring Polarization of Topics across Different Corpora. - Federico Bianchi 001; Marco Marelli; Paolo Nicoli; Matteo Palmonari (EMNLP (1), 2021)

NEST: Neural Soft Type Constraints to Improve Entity Linking in Tables. - Vincenzo Cutrona; Gianluca Puleri; Federico Bianchi 001; Matteo Palmonari (SEMANTiCS, 2021)

Language in a (Search) Box: Grounding Language Learning in Real-World Human-Machine Interaction. - Federico Bianchi 001; Ciro Greco; Jacopo Tagliabue (NAACL-HLT, 2021)

Query2Prod2Vec: Grounded Word Embeddings for eCommerce. - Federico Bianchi 001; Jacopo Tagliabue; Bingqing Yu (NAACL-HLT (Industry Papers), 2021)

HONEST: Measuring Hurtful Sentence Completion in Language Models. - Debora Nozza; Federico Bianchi 001; Dirk Hovy (NAACL-HLT, 2021)

FEEL-IT: Emotion and Sentiment Classification for the Italian Language. - Federico Bianchi 001; Debora Nozza; Dirk Hovy (WASSA@EACL, 2021)

MilaNLP @ WASSA: Does BERT Feel Sad When You Cry? - Tommaso Fornaciari; Federico Bianchi 001; Debora Nozza; Dirk Hovy (WASSA@EACL, 2021)

Universal Joy A Data Set and Results for Classifying Emotions Across Languages. - Sotiris Lamprinidis; Federico Bianchi 001; Daniel Hardt; Dirk Hovy (WASSA@EACL, 2021)

Towards bridging the neuro-symbolic gap: deep deductive reasoners. - Monireh Ebrahimi; Aaron Eberhart; Federico Bianchi 001; Pascal Hitzler (Appl. Intell., 2021)

Words with Consistent Diachronic Usage Patterns are Learned Earlier: A Computational Analysis Using Temporally Aligned Word Embeddings. - Giovanni Cassani; Federico Bianchi 001; Marco Marelli (Cogn. Sci., 2021)

SIGIR 2021 E-Commerce Workshop Data Challenge. - Jacopo Tagliabue; Ciro Greco; Jean-Francis Roy; Bingqing Yu; Patrick John Chia; Federico Bianchi 001; Giovanni Cassani (CoRR, 2021)

Contrastive Language-Image Pre-training for the Italian Language. - Federico Bianchi 001; Giuseppe Attanasio; Raphael Pisoni; Silvia Terragni; Gabriele Sarti; Sri Lakshmi (CoRR, 2021)

Language Invariant Properties in Natural Language Processing. - Federico Bianchi 001; Debora Nozza; Dirk Hovy (CoRR, 2021)

Logic Tensor Networks: Theory and Applications. - Luciano Serafini; Artur S. d'Avila Garcez; Samy Badreddine; Ivan Donadello; Michael Spranger; Federico Bianchi 001 (Neuro-Symbolic Artificial Intelligence, 2021)

Tough Tables: Carefully Evaluating Entity Linking for Tabular Data. - Vincenzo Cutrona; Federico Bianchi 001; Ernesto Jiménez-Ruiz; Matteo Palmonari (Zenodo, 2021)

Tough Tables: Carefully Evaluating Entity Linking for Tabular Data. - Vincenzo Cutrona; Federico Bianchi 001; Ernesto Jiménez-Ruiz; Matteo Palmonari (Zenodo, 2021)

EvalRS: a rounded evaluation of recommender systems. - Jacopo Tagliabue; Federico Bianchi 001; Tobias Schnabel; Giuseppe Attanasio; Ciro Greco; Gabriel de Souza P. Moreira; Patrick John Chia (CIKM Workshops, 2022)

Twitter-Demographer: A Flow-based Tool to Enrich Twitter Data. - Federico Bianchi 001; Vincenzo Cutrona; Dirk Hovy (EMNLP (Demos), 2022)

"It's Not Just Hate": A Multi-Dimensional Perspective on Detecting Harmful Speech Online. - Federico Bianchi 001; Stefanie Anja Hills; Patrícia G. C. Rossini; Dirk Hovy; Rebekah Tromble; Nava Tintarev (EMNLP, 2022)

SocioProbe: What, When, and Where Language Models Learn about Sociodemographics. - Anne Lauscher; Federico Bianchi 001; Samuel R. Bowman; Dirk Hovy (EMNLP, 2022)

Data-Efficient Strategies for Expanding Hate Speech Detection into Under-Resourced Languages. - Paul Röttger; Debora Nozza; Federico Bianchi 001; Dirk Hovy (EMNLP, 2022)

Measuring Harmful Sentence Completion in Language Models for LGBTQIA+ Individuals. - Debora Nozza; Federico Bianchi 001; Anne Lauscher; Dirk Hovy (LT-EDI, 2022)

MilaNLP at SemEval-2022 Task 5: Using Perceiver IO for Detecting Misogynous Memes with Text and Image Modalities. - Giuseppe Attanasio; Debora Nozza; Federico Bianchi 001 (SemEval@NAACL, 2022)

XLM-EMO: Multilingual Emotion Prediction in Social Media Text. - Federico Bianchi 001; Debora Nozza; Dirk Hovy (WASSA@ACL, 2022)

Beyond NDCG: Behavioral Testing of Recommender Systems with RecList. - Patrick John Chia; Jacopo Tagliabue; Federico Bianchi 001; Chloe He 001; Brian Ko (WWW (Companion Volume), 2022)

"Does it come in black?" CLIP-like models are zero-shot recommenders. - Patrick John Chia; Jacopo Tagliabue; Federico Bianchi 001; Ciro Greco; Diogo Gonçalves 007 (CoRR, 2022)

FashionCLIP: Connecting Language and Images for Product Representations. - Patrick John Chia; Giuseppe Attanasio; Federico Bianchi 001; Silvia Terragni; Ana Rita Magalhães; Diogo Gonçalves 007; Ciro Greco; Jacopo Tagliabue (CoRR, 2022)

Is It Worth the (Environmental) Cost? Limited Evidence for the Benefits of Diachronic Continuous Training. - Giuseppe Attanasio; Debora Nozza; Federico Bianchi 001; Dirk Hovy (CoRR, 2022)

ProSiT! Latent Variable Discovery with PROgressive SImilarity Thresholds. - Tommaso Fornaciari; Dirk Hovy; Federico Bianchi 001 (CoRR, 2022)

Gender and Age Bias in Commercial Machine Translation. - Federico Bianchi 001; Tommaso Fornaciari; Dirk Hovy; Debora Nozza (Towards Responsible Machine Translation, 2023)

Contrastive Language-Image Pre-training for the Italian Language. - Federico Bianchi 001; Giuseppe Attanasio; Raphael Pisoni; Silvia Terragni; Gabriele Sarti; Dario Balestri (CLiC-it, 2023)

Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. - Federico Bianchi 001; Pratyusha Kalluri; Esin Durmus; Faisal Ladhak; Myra Cheng; Debora Nozza; Tatsunori Hashimoto; Dan Jurafsky; James Zou 001; Aylin Caliskan (FAccT, 2023)

When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It? - Mert Yüksekgönül; Federico Bianchi 001; Pratyusha Kalluri; Dan Jurafsky; James Zou 001 (ICLR, 2023)

EvalRS 2023: Well-Rounded Recommender Systems for Real-World Deployments. - Federico Bianchi 001; Patrick John Chia; Jacopo Tagliabue; Ciro Greco; Gabriel de Souza P. Moreira; Davide Eynard; Fahd Husain; Claudio Pomo (KDD, 2023)

Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political Discussion. - Rishav Hada; Amir Ebrahimi Fard; Sarah Shugars; Federico Bianchi 001; Patrícia G. C. Rossini; Dirk Hovy; Rebekah Tromble; Nava Tintarev (WSDM, 2023)

E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender Systems. - Patrick John Chia; Giuseppe Attanasio; Jacopo Tagliabue; Federico Bianchi 001; Ciro Greco; Gabriel de Souza P. Moreira; Davide Eynard; Fahd Husain (CoRR, 2023)

Viewpoint: Artificial Intelligence Accidents Waiting to Happen? - Federico Bianchi 001; Amanda Cercas Curry; Dirk Hovy (J. Artif. Intell. Res., 2023)

A challenge for rounded evaluation of recommender systems. - Jacopo Tagliabue; Federico Bianchi 001; Tobias Schnabel; Giuseppe Attanasio; Ciro Greco; Gabriel de Souza P. Moreira; Patrick John Chia (Nat. Mac. Intell., 2023)

Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. - Federico Bianchi 001; Mirac Suzgun; Giuseppe Attanasio; Paul Röttger; Dan Jurafsky; Tatsunori Hashimoto; James Zou 001 (ICLR, 2024)

How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis. - Federico Bianchi 001; Patrick John Chia; Mert Yüksekgönül; Jacopo Tagliabue; Dan Jurafsky; James Zou 001 (ICML, 2024)

XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models. - Paul Röttger; Hannah Kirk; Bertie Vidgen; Giuseppe Attanasio; Federico Bianchi 001; Dirk Hovy (NAACL-HLT, 2024)

Large Language Models are Vulnerable to Bait-and-Switch Attacks for Generating Harmful Content. - Federico Bianchi 001; James Zou 001 (CoRR, 2024)

TextGrad: Automatic "Differentiation" via Text. - Mert Yüksekgönül; Federico Bianchi 001; Joseph Boen; Sheng Liu; Zhi Huang; Carlos Guestrin; James Zou 001 (CoRR, 2024)

h4rm3l: A Dynamic Benchmark of Composable Jailbreak Attacks for LLM Safety Assessment. - Moussa Koulako Bala Doumbouya; Ananjan Nandi; Gabriel Poesia; Davide Ghilardi; Anna Goldie; Federico Bianchi 001; Dan Jurafsky; Christopher D. Manning (CoRR, 2024)

Belief in the Machine: Investigating Epistemological Blind Spots of Language Models. - Mirac Suzgun; Tayfun Gur; Federico Bianchi 001; Daniel E. Ho; Thomas Icard; Dan Jurafsky; James Zou 001 (CoRR, 2024)

Author Correction: A challenge for rounded evaluation of recommender systems. - Jacopo Tagliabue; Federico Bianchi 001; Tobias Schnabel; Giuseppe Attanasio; Ciro Greco; Gabriel de Souza P. Moreira; Patrick John Chia (Nat. Mac. Intell., 2024)

h4rm3l: A Language for Composable Jailbreak Attack Synthesis. - Moussa Koulako Bala Doumbouya; Ananjan Nandi; Gabriel Poesia; Davide Ghilardi; Anna Goldie; Federico Bianchi 001; Dan Jurafsky; Christopher D. Manning (ICLR, 2025)

Optimizing generative AI by backpropagating language model feedback. - Mert Yüksekgönül; Federico Bianchi 001; Joseph Boen; Sheng Liu; Pan Lu; Zhi Huang; Carlos Guestrin; James Zou 001 (Nat., 2025)

Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory. - Mirac Suzgun; Mert Yüksekgönül; Federico Bianchi 001; Dan Jurafsky; James Zou 001 (CoRR, 2025)

Labeling Messages as AI-Generated Does Not Reduce Their Persuasive Effects. - Isabel O. Gallegos; Chen Shani; Weiyan Shi; Federico Bianchi 001; Izzy Gainsburg; Dan Jurafsky; Robb Willer (CoRR, 2025)