Tobias Schnabel

54 papers A* 10A 8B 1Misc 1Journal 27Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs. AAAI Trenton Chang, Tobias Schnabel, Adith Swaminathan, Jenna Wiens
2026	J	`jnl`	Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs. CoRR Kiran Tomlinson, Tobias Schnabel, Adith Swaminathan, Jennifer Neville
2025	J	`jnl`	A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs. CoRR Trenton Chang, Tobias Schnabel, Adith Swaminathan, Jenna Wiens
2025	J	`jnl`	Lost in Transmission: When and Why LLMs Fail to Reason Globally. CoRR Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan, Jennifer Neville
2024	J	`jnl`	Author Correction: A challenge for rounded evaluation of recommender systems. Nat. Mac. Intell. Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
2024	J	`jnl`	Introduction to the Special Issue on Causal Inference for Recommender Systems. Trans. Recomm. Syst. Yongfeng Zhang, Xu Chen, Da Xu, Tobias Schnabel
2024	A	`conf`	On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots. UAI Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
2024	J	`jnl`	On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
2024	J	`jnl`	Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. CoRR Tobias Schnabel, Jennifer Neville
2024	—	`conf`	Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. EMNLP (Findings) Tobias Schnabel, Jennifer Neville
2023	J	`jnl`	A challenge for rounded evaluation of recommender systems. Nat. Mac. Intell. Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
2023	—	`conf`	Foreword for Workshop on Decision Making for Information Retrieval and Recommender Systems. WWW (Companion Volume) Da Xu, Tobias Schnabel, Xiquan Cui, Sarah Dean, Aniket Deshmukh, Bo Yang, Shipeng Yu
2023	A*	`conf`	When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? SIGIR Yushun Dong, Jundong Li, Tobias Schnabel
2023	J	`jnl`	When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? CoRR Yushun Dong, Jundong Li, Tobias Schnabel
2022	J	`jnl`	EvalRS: a Rounded Evaluation of Recommender Systems. CoRR Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
2022	—	`conf`	EvalRS: a rounded evaluation of recommender systems. CIKM Workshops Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia
2022	A	`conf`	HINT: Integration Testing for AI-based features with Humans in the Loop. IUI Quan Ze Chen, Tobias Schnabel, Besmira Nushi, Saleema Amershi
2022	J	`jnl`	Lightweight Compositional Embeddings for Incremental Streaming Recommendation. CoRR Mengyue Hang, Tobias Schnabel, Longqi Yang, Jennifer Neville
2022	J	`jnl`	Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates. CoRR Tobias Schnabel, Mengting Wan, Longqi Yang
2022	J	`jnl`	SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization. Trans. Assoc. Comput. Linguistics Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
2022	J	`jnl`	Where Do We Go From Here? Guidelines For Offline Recommender Evaluation. CoRR Tobias Schnabel
2021	—	`conf`	Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text. ACL/IJCNLP (1) Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
2021	J	`jnl`	Keep it Simple: Unsupervised Simplification of Multi-Paragraph Text. CoRR Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
2021	A	`conf`	Local Factor Models for Large-Scale Inductive Recommendation. RecSys Longqi Yang, Tobias Schnabel, Paul N. Bennett, Susan T. Dumais
2021	J	`jnl`	SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization. CoRR Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
2020	A	`conf`	"Who doesn't like dinosaurs?" Finding and Eliciting Richer Preferences for Recommendation. RecSys Tobias Schnabel, Gonzalo A. Ramos, Saleema Amershi
2020	A	`conf`	Debiasing Item-to-Item Recommendations With Small Annotated Datasets. RecSys Tobias Schnabel, Paul N. Bennett
2020	A*	`conf`	The Impact of More Transparent Interfaces on Behavior in Personalized Recommendation. SIGIR Tobias Schnabel, Saleema Amershi, Paul N. Bennett, Peter Bailey, Thorsten Joachims
2019	A*	`conf`	Deep Generalized Method of Moments for Instrumental Variable Analysis. NeurIPS Andrew Bennett, Nathan Kallus, Tobias Schnabel
2019	J	`jnl`	Deep Generalized Method of Moments for Instrumental Variable Analysis. CoRR Andrew Bennett, Nathan Kallus, Tobias Schnabel
2019	A	`conf`	Shaping Feedback Data in Recommender Systems with Interventions Based on Information Foraging Theory. WSDM Tobias Schnabel, Paul N. Bennett, Thorsten Joachims
2018	—	`—`	Improving Machine Learning Beyond the Algorithm. Tobias Schnabel
2018	J	`jnl`	Improving Recommender Systems Beyond the Algorithm. CoRR Tobias Schnabel, Paul N. Bennett, Thorsten Joachims
2018	A	`conf`	Short-Term Satisfaction and Long-Term Coverage: Understanding How Users Tolerate Algorithmic Exploration. WSDM Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims
2018	A*	`conf`	Unbiased Learning-to-Rank with Biased Feedback. IJCAI Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
2017	J	`jnl`	A preference elicitation interface for collecting dense recommender datasets with rich user information. CoRR Pantelis P. Analytis, Tobias Schnabel, Stefan M. Herzog, Daniel Barkoczi, Thorsten Joachims
2017	A*	`conf`	Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers. KDD Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims
2017	J	`jnl`	Effective Evaluation using Logged Bandit Feedback from Multiple Loggers. CoRR Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims
2017	A	`conf`	Unbiased Learning-to-Rank with Biased Feedback. WSDM Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
2016	J	`jnl`	Online Updating of Word Representations for Part-of-Speech Tagging. CoRR Wenpeng Yin, Tobias Schnabel, Hinrich Schütze
2016	A*	`conf`	Recommendations as Treatments: Debiasing Learning and Evaluation. ICML Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
2016	J	`jnl`	Recommendations as Treatments: Debiasing Learning and Evaluation. CoRR Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
2016	Misc	`conf`	Unbiased Comparative Evaluation of Ranking Functions. ICTIR Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
2016	J	`jnl`	Unbiased Comparative Evaluation of Ranking Functions. CoRR Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
2016	J	`jnl`	Unbiased Learning-to-Rank with Biased Feedback. CoRR Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
2016	A*	`conf`	Using Shortlists to Support Decision Making and Improve Recommender System Performance. WWW Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims
2015	A*	`conf`	Evaluation methods for unsupervised word embeddings. EMNLP Tobias Schnabel, Igor Labutov, David M. Mimno, Thorsten Joachims
2015	A*	`conf`	Online Updating of Word Representations for Part-of-Speech Tagging. EMNLP Wenpeng Yin, Tobias Schnabel, Hinrich Schütze
2015	J	`jnl`	Towards a Better Understanding of Predict and Count Models. CoRR S. Sathiya Keerthi, Tobias Schnabel, Rajiv Khanna
2015	—	`conf`	Unbiased Ranking Evaluation on a Budget. WWW (Companion Volume) Tobias Schnabel, Adith Swaminathan, Thorsten Joachims
2015	J	`jnl`	Using Shortlists to Support Decision Making and Improve Recommender System Performance. CoRR Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims
2014	J	`jnl`	FLORS: Fast and Simple Domain Adaptation for Part-of-Speech Tagging. Trans. Assoc. Comput. Linguistics Tobias Schnabel, Hinrich Schütze
2013	—	`conf`	Stable Coactive Learning via Perturbation. ICML (3) Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel
2013	B	`conf`	Towards Robust Cross-Domain Domain Adaptation for Part-of-Speech Tagging. IJCNLP Tobias Schnabel, Hinrich Schütze