Spam detection using web page content: a new battleground. - Marco Túlio Ribeiro; Pedro Henrique Calais Guerra; Leonardo Vilela; Adriano Veloso; Dorgival O. Guedes; Wagner Meira Jr.; Marcelo H. P. C. Chaves; Klaus Steding-Jessen; Cristine Hoepers (CEAS, 2011)

Pareto-efficient hybridization for multi-objective recommender systems. - Marco Túlio Ribeiro; Anísio Lacerda; Adriano Veloso; Nivio Ziviani (RecSys, 2012)

A Holistic Hybrid Algorithm for User Recommendation on Twitter. - Sara Guimarães; Marco Túlio Ribeiro; Renato M. Assunção; Wagner Meira Jr. (J. Inf. Data Manag., 2013)

Multiobjective Pareto-Efficient Approaches for Recommender Systems. - Marco Túlio Ribeiro; Nivio Ziviani; Edleno Silva de Moura; Itamar Hata; Anísio Lacerda; Adriano Veloso (ACM Trans. Intell. Syst. Technol., 2014)

"Why Should I Trust You?": Explaining the Predictions of Any Classifier. - Marco Túlio Ribeiro; Sameer Singh 001; Carlos Guestrin (KDD, 2016)

Programs as Black-Box Explanations. - Sameer Singh 001; Marco Túlio Ribeiro; Carlos Guestrin (CoRR, 2016)

Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance. - Marco Túlio Ribeiro; Sameer Singh 001; Carlos Guestrin (CoRR, 2016)

Model-Agnostic Interpretability of Machine Learning. - Marco Túlio Ribeiro; Sameer Singh 001; Carlos Guestrin (CoRR, 2016)

Anchors: High-Precision Model-Agnostic Explanations. - Marco Túlio Ribeiro; Sameer Singh 001; Carlos Guestrin (AAAI, 2018)

Semantically Equivalent Adversarial Rules for Debugging NLP models. - Marco Túlio Ribeiro; Sameer Singh 001; Carlos Guestrin (ACL (1), 2018)

Model-Agnostic Explanations and Evaluation of Machine Learning. - Marco Túlio Ribeiro (2018)

Are Red Roses Red? Evaluating Consistency of Question-Answering Models. - Marco Túlio Ribeiro; Carlos Guestrin; Sameer Singh 001 (ACL (1), 2019)

Errudite: Scalable, Reproducible, and Testable Error Analysis. - Tongshuang Wu; Marco Túlio Ribeiro; Jeffrey Heer; Daniel S. Weld (ACL (1), 2019)

Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. - Marco Túlio Ribeiro; Tongshuang Wu; Carlos Guestrin; Sameer Singh 001 (ACL, 2020)

SQuINTing at VQA Models: Introspecting VQA Models With Sub-Questions. - Ramprasaath R. Selvaraju; Purva Tendulkar; Devi Parikh; Eric Horvitz; Marco Túlio Ribeiro; Besmira Nushi; Ece Kamar (CVPR, 2020)

Intelligible and Explainable Machine Learning: Best Practices and Practical Challenges. - Rich Caruana; Scott M. Lundberg; Marco Túlio Ribeiro; Harsha Nori; Samuel Jenkins (KDD, 2020)

Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models. - Tongshuang Wu; Marco Túlio Ribeiro; Jeffrey Heer; Daniel S. Weld (ACL/IJCNLP (1), 2021)

Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. - Gagan Bansal; Tongshuang Wu; Joyce Zhou; Raymond Fok; Besmira Nushi; Ece Kamar; Marco Túlio Ribeiro; Daniel S. Weld (CHI, 2021)

Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract). - Marco Túlio Ribeiro; Tongshuang Wu; Carlos Guestrin; Sameer Singh 001 (IJCAI, 2021)

Polyjuice: Automated, General-purpose Counterfactual Generation. - Tongshuang Wu; Marco Túlio Ribeiro; Jeffrey Heer; Daniel S. Weld (CoRR, 2021)

Do Feature Attribution Methods Correctly Attribute Features? - Yilun Zhou; Serena Booth; Marco Túlio Ribeiro; Julie Shah (AAAI, 2022)

Adaptive Testing and Debugging of NLP Models. - Marco Túlio Ribeiro; Scott M. Lundberg (ACL (1), 2022)

Fixing Model Bugs with Natural Language Patches. - Shikhar Murty; Christopher D. Manning; Scott M. Lundberg; Marco Túlio Ribeiro (EMNLP, 2022)

ExSum: From Local Explanations to Model Understanding. - Yilun Zhou; Marco Túlio Ribeiro; Julie Shah (NAACL-HLT, 2022)

Evaluating Systemic Error Detection Methods using Synthetic Images. - Gregory Plumb; Nari Johnson; Ángel Alexander Cabrera; Marco Túlio Ribeiro; Ameet Talwalkar (CoRR, 2022)

Editing Models with Task Arithmetic. - Gabriel Ilharco; Marco Túlio Ribeiro; Mitchell Wortsman; Suchin Gururangan; Ludwig Schmidt; Hannaneh Hajishirzi; Ali Farhadi (CoRR, 2022)

Finding and Fixing Spurious Patterns with Explanations. - Gregory Plumb; Marco Túlio Ribeiro; Ameet Talwalkar (Trans. Mach. Learn. Res., 2022)

Targeted Data Generation: Finding and Fixing Model Weaknesses. - Zexue He; Marco Túlio Ribeiro; Fereshte Khani (ACL (1), 2023)

Supporting Human-AI Collaboration in Auditing LLMs with LLMs. - Charvi Rastogi; Marco Túlio Ribeiro; Nicholas King; Harsha Nori; Saleema Amershi (AIES, 2023)

Adaptive Testing of Computer Vision Models. - Irena Gao; Gabriel Ilharco; Scott M. Lundberg; Marco Túlio Ribeiro (ICCV, 2023)

Editing models with task arithmetic. - Gabriel Ilharco; Marco Túlio Ribeiro; Mitchell Wortsman; Ludwig Schmidt; Hannaneh Hajishirzi; Ali Farhadi (ICLR, 2023)

ScatterShot: Interactive In-context Example Curation for Text Transformation. - Sherry Wu; Hua Shen 005; Daniel S. Weld; Jeffrey Heer; Marco Túlio Ribeiro (IUI, 2023)

Collaborative Alignment of NLP Models. - Fereshte Khani; Marco Túlio Ribeiro (NeurIPS, 2023)

ART: Automatic multi-step reasoning and tool-use for large language models. - Bhargavi Paranjape; Scott M. Lundberg; Sameer Singh 001; Hannaneh Hajishirzi; Luke Zettlemoyer; Marco Túlio Ribeiro (CoRR, 2023)

Sparks of Artificial General Intelligence: Early experiments with GPT-4. - Sébastien Bubeck; Varun Chandrasekaran; Ronen Eldan; Johannes Gehrke; Eric Horvitz; Ece Kamar; Peter Lee; Yin Tat Lee; Yuanzhi Li; Scott M. Lundberg; Harsha Nori; Hamid Palangi; et al. (CoRR, 2023)

Supporting Human-AI Collaboration in Auditing LLMs with LLMs. - Charvi Rastogi; Marco Túlio Ribeiro; Nicholas King; Saleema Amershi (CoRR, 2023)

Collaborative Development of NLP models. - Fereshte Khani; Marco Túlio Ribeiro (CoRR, 2023)

AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms. - Zana Buçinca; Chau Minh Pham; Maurice Jakesch; Marco Túlio Ribeiro; Alexandra Olteanu; Saleema Amershi (CoRR, 2023)

What Did My AI Learn? How Data Scientists Make Sense of Model Behavior. - Ángel Alexander Cabrera; Marco Túlio Ribeiro; Bongshin Lee; Robert DeLine; Adam Perer; Steven Mark Drucker (ACM Trans. Comput. Hum. Interact., 2023)

Sequential Diagnosis with Language Models. - Harsha Nori; Mayank Daswani; Christopher Kelly; Scott M. Lundberg; Marco Túlio Ribeiro; Marc Wilson; Xiaoxuan Liu; Viknesh Sounderajah; Jonathan Carlson; Matthew P. Lungren; Bay Gross; Peter Hames; et al. (CoRR, 2025)