Schnabel, Tobias

Unbiased Learning-to-Rank with Biased Feedback

Joachims, T., Swaminathan, A., & Schnabel, T. (2017) · Proceedings of the Tenth ACM International Conference on Web Search and Data Mining

Information Retrieval and Search BehaviorRecommender Systems and Techniques

Cited by 531

SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization

Laban, P., Schnabel, T., Bennett, P. N., & Hearst, M. A. (2022) · Transactions of the Association for Computational Linguistics

Topic ModelingAdvanced Text Analysis Techniques

Cited by 238

SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization

Laban, P., Schnabel, T., Bennett, P. N., & Hearst, M. A. (2021) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 38

Local Factor Models for Large-Scale Inductive Recommendation

Yang, L., Schnabel, T., Bennett, P. N., & Dumais, S. (2021) · Fifteenth ACM Conference on Recommender Systems

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 6

LLMs Corrupt Your Documents When You Delegate

Laban, P., Schnabel, T., & Neville, J. (2026) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1

On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots

Herlihy, C., Neville, J., Schnabel, T., & Swaminathan, A. (2024) · arXiv

Recommender Systems and TechniquesSpeech and dialogue systems

Cited by 1