Tobias Schnabel

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 38

Top Topics

Ranking Functions

Personalized Recommendation

Domain Adaptation

Incremental Updates

Top Venues

Publications

Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
Author Correction: A challenge for rounded evaluation of recommender systems. Nat. Mac. Intell. 6 (3) (2024)
Tobias Schnabel, Jennifer Neville
Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. CoRR (2024)
Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR (2024)
Da Xu, Tobias Schnabel, Xiquan Cui, Sarah Dean, Aniket Deshmukh, Bo Yang, Shipeng Yu
Foreword for Workshop on Decision Making for Information Retrieval and Recommender Systems. WWW (Companion Volume) (2023)
Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
A challenge for rounded evaluation of recommender systems. Nat. Mac. Intell. 5 (2) (2023)
Yushun Dong, Jundong Li, Tobias Schnabel
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? SIGIR (2023)
Yushun Dong, Jundong Li, Tobias Schnabel
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? CoRR (2023)
Mengyue Hang, Tobias Schnabel, Longqi Yang, Jennifer Neville
Lightweight Compositional Embeddings for Incremental Streaming Recommendation. CoRR (2022)
Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
EvalRS: a Rounded Evaluation of Recommender Systems. CoRR (2022)
Tobias Schnabel, Mengting Wan, Longqi Yang
Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates. CoRR (2022)
Quan Ze Chen, Tobias Schnabel, Besmira Nushi, Saleema Amershi
HINT: Integration Testing for AI-based features with Humans in the Loop. IUI (2022)
Tobias Schnabel
Where Do We Go From Here? Guidelines For Offline Recommender Evaluation. CoRR (2022)
Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
EvalRS: a rounded evaluation of recommender systems. CIKM Workshops (2022)
Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization. Trans. Assoc. Comput. Linguistics 10 (2022)
Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
Keep it Simple: Unsupervised Simplification of Multi-Paragraph Text. CoRR (2021)
Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization. CoRR (2021)
Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text. ACL/IJCNLP (1) (2021)
Longqi Yang, Tobias Schnabel, Paul N. Bennett, Susan T. Dumais
Local Factor Models for Large-Scale Inductive Recommendation. RecSys (2021)
Tobias Schnabel, Gonzalo A. Ramos, Saleema Amershi
"Who doesn't like dinosaurs?" Finding and Eliciting Richer Preferences for Recommendation. RecSys (2020)
Tobias Schnabel, Saleema Amershi, Paul N. Bennett, Peter Bailey, Thorsten Joachims
The Impact of More Transparent Interfaces on Behavior in Personalized Recommendation. SIGIR (2020)
Tobias Schnabel, Paul N. Bennett
Debiasing Item-to-Item Recommendations With Small Annotated Datasets. RecSys (2020)
Andrew Bennett, Nathan Kallus, Tobias Schnabel
Deep Generalized Method of Moments for Instrumental Variable Analysis. CoRR (2019)
Tobias Schnabel, Paul N. Bennett, Thorsten Joachims
Shaping Feedback Data in Recommender Systems with Interventions Based on Information Foraging Theory. WSDM (2019)
Andrew Bennett, Nathan Kallus, Tobias Schnabel
Deep Generalized Method of Moments for Instrumental Variable Analysis. NeurIPS (2019)
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
Unbiased Learning-to-Rank with Biased Feedback. IJCAI (2018)
Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims
Short-Term Satisfaction and Long-Term Coverage: Understanding How Users Tolerate Algorithmic Exploration. WSDM (2018)
Tobias Schnabel, Paul N. Bennett, Thorsten Joachims
Improving Recommender Systems Beyond the Algorithm. CoRR (2018)
Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims
Effective Evaluation using Logged Bandit Feedback from Multiple Loggers. CoRR (2017)
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
Unbiased Learning-to-Rank with Biased Feedback. WSDM (2017)
Pantelis P. Analytis, Tobias Schnabel, Stefan Herzog, Daniel Barkoczi, Thorsten Joachims
A preference elicitation interface for collecting dense recommender datasets with rich user information. CoRR (2017)
Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims
Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers. KDD (2017)
Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims
Using Shortlists to Support Decision Making and Improve Recommender System Performance. WWW (2016)
Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
Unbiased Comparative Evaluation of Ranking Functions. ICTIR (2016)
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
Unbiased Learning-to-Rank with Biased Feedback. CoRR (2016)
Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
Unbiased Comparative Evaluation of Ranking Functions. CoRR (2016)
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
Recommendations as Treatments: Debiasing Learning and Evaluation. CoRR (2016)
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
Recommendations as Treatments: Debiasing Learning and Evaluation. ICML (2016)
Wenpeng Yin, Tobias Schnabel, Hinrich Schütze
Online Updating of Word Representations for Part-of-Speech Tagging. CoRR (2016)
Tobias Schnabel, Igor Labutov, David M. Mimno, Thorsten Joachims
Evaluation methods for unsupervised word embeddings. EMNLP (2015)
Tobias Schnabel, Adith Swaminathan, Thorsten Joachims
Unbiased Ranking Evaluation on a Budget. WWW (Companion Volume) (2015)
S. Sathiya Keerthi, Tobias Schnabel, Rajiv Khanna
Towards a Better Understanding of Predict and Count Models. CoRR (2015)
Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims
Using Shortlists to Support Decision Making and Improve Recommender System Performance. CoRR (2015)
Wenpeng Yin, Tobias Schnabel, Hinrich Schütze
Online Updating of Word Representations for Part-of-Speech Tagging. EMNLP (2015)
Tobias Schnabel, Hinrich Schütze
FLORS: Fast and Simple Domain Adaptation for Part-of-Speech Tagging. Trans. Assoc. Comput. Linguistics 2 (2014)
Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel
Stable Coactive Learning via Perturbation. ICML (3) (2013)
Tobias Schnabel, Hinrich Schütze
Towards Robust Cross-Domain Domain Adaptation for Part-of-Speech Tagging. IJCNLP (2013)