Scott Sanner

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 147

Top Venues

Publications

Armin Toroghi, Willis Guo, Mohammad Mahdi Abdollah Pour, Scott Sanner
Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering. CoRR (2024)
David Eric Austin, Anton Korikov, Armin Toroghi, Scott Sanner
Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation. CoRR (2024)
Michael Gimelfarb, Ayal Taitler, Scott Sanner
Constraint-Generation Policy Optimization (CGPO): Nonlinear Programming for Policy Optimization in Mixed Discrete-Continuous MDPs. CoRR (2024)
Ayal Taitler, Ron Alford, Joan Espasa, Gregor Behnke, Daniel Fiser, Michael Gimelfarb, Florian Pommerening, Scott Sanner, Enrico Scala, Dominik Schreiber, Javier Segovia-Aguas, Jendrik Seipp
The 2023 International Planning Competition. AI Mag. 45 (2) (2024)
Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias Boutros Khalil
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations. Trans. Mach. Learn. Res. 2024 (2024)
Michael Gimelfarb, Ayal Taitler, Scott Sanner
JaxPlan and GurobiPlan: Optimization Baselines for Replanning in Discrete and Mixed Discrete-Continuous Probabilistic Domains. ICAPS (2024)
Sara Kemper, Justin Cui, Kai Dicarlantonio, Kathy Lin, Danjie Tang, Anton Korikov, Scott Sanner
Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking. SIGIR (2024)
Armin Toroghi, Scott Sanner
Bayesian Inference with Complex Knowledge Graph Evidence. AAAI (2024)
Sara Kemper, Justin Cui, Kai Dicarlantonio, Kathy Lin, Danjie Tang, Anton Korikov, Scott Sanner
Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking. CoRR (2024)
Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). KDD (2024)
Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). CoRR (2024)
Willis Guo, Armin Toroghi, Scott Sanner
CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail Knowledge. CoRR (2024)
Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Armin Toroghi, Anton Korikov, Ali Pesaranghader, Touqir Sajed, Manasa Bharadwaj, Borislav Mavrin, Scott Sanner
Self-supervised Contrastive BERT Fine-tuning for Fusion-Based Reviewed-Item Retrieval. ECIR (1) (2023)
Siow Meng Low, Akshat Kumar, Scott Sanner
Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects. ICAPS (2023)
Siow Meng Low, Akshat Kumar, Scott Sanner
Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects. CoRR (2023)
Ilia Smirnov, Scott Sanner, Baher Abdulhai
A Case for Monte Carlo Tree Search in Adaptive Traffic Signal Control: Modifiability, Interpretability and Generalization. ITSC (2023)
Aravinth Chembu, Scott Sanner
A Generalized Framework for Predictive Clustering and Optimization. CoRR (2023)
Griffin Floto, Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Zhenwei Tang, Ali Pesaranghader, Manasa Bharadwaj, Scott Sanner
DiffuDetox: A Mixed Diffusion Model for Text Detoxification. ACL (Findings) (2023)
Griffin Floto, Thorsteinn Jonsson, Mihai Nica, Scott Sanner, Eric Zhengyu Zhu
Diffusion on the Probability Simplex. CoRR (2023)
Armin Toroghi, Griffin Floto, Zhenwei Tang, Scott Sanner
Bayesian Knowledge-driven Critiquing with Indirect Evidence. CoRR (2023)
Xiaocan Li, Ray Coden Mercurius, Ayal Taitler, Xiaoyu Wang, Mohammad Noaeen, Scott Sanner, Baher Abdulhai
Perimeter Control Using Deep Reinforcement Learning: A Model-free Approach towards Homogeneous Flow Rate Optimization. CoRR (2023)
Jihwan Jeong, Scott Sanner, Akshat Kumar
A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. CPAIOR (2023)
Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang, Scott Sanner
LogicRec: Recommendation with Users' Logical Requirements. CoRR (2023)
Griffin Floto, Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Zhenwei Tang, Ali Pesaranghader, Manasa Bharadwaj, Scott Sanner
DiffuDetox: A Mixed Diffusion Model for Text Detoxification. CoRR (2023)
Aravinth Chembu, Scott Sanner, Hassan Khurram, Akshat Kumar
Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming. AAAI (2023)
Armin Toroghi, Griffin Floto, Zhenwei Tang, Scott Sanner
Bayesian Knowledge-driven Critiquing with Indirect Evidence. SIGIR (2023)
Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Armin Toroghi, Anton Korikov, Ali Pesaranghader, Touqir Sajed, Manasa Bharadwaj, Borislav Mavrin, Scott Sanner
Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval. CoRR (2023)
Ruiwen Li, Zheda Mai, Zhibo Zhang, Jongseong Jang, Scott Sanner
TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation. J. Vis. Commun. Image Represent. 92 (2023)
Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Manasa Bharadwaj, Nikhil Verma, Ali Pesaranghader, Scott Sanner
COUNT: COntrastive UNlikelihood Text Style Transfer for Text Detoxification. EMNLP (Findings) (2023)
Xiaoyu Wang, Ayal Taitler, Ilia Smirnov, Scott Sanner, Baher Abdulhai
eMARLIN+: Overcoming Partial-Observability Caused by Sensor Limitations and Short Detection Ranges in Traffic Signal Control. ITSC (2023)
Xiaocan Li, Ray Coden Mercurius, Ayal Taitler, Xiaoyu Wang, Mohammad Noaeen, Scott Sanner, Baher Abdulhai
Perimeter Control Using Deep Reinforcement Learning: A Model-Free Approach Towards Homogeneous Flow Rate Optimization. ITSC (2023)
Aravinth Chembu, Scott Sanner, Elias B. Khalil
Scalable and Near-Optimal ε-Tube Clusterwise Regression. CPAIOR (2023)
Ta Jiun Ting, Xiaocan Li, Scott Sanner, Baher Abdulhai
Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction. CoRR (2023)
Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. ICLR (2023)
Tongzi Wu, Yuhao Zhou, Wang Ling, Hojin Yang, Joana Veloso, Lin Sun, Ruixin Huang, Norberto Guimaraes, Scott Sanner
Towards Dialogue Modeling Beyond Text. ICASSP (2023)
Sebastian Junges, Joost-Pieter Katoen, Scott Sanner, Guy Van den Broeck, Bahare Salmani
Scalable Analysis of Probabilistic Models and Programs (Dagstuhl Seminar 23241). Dagstuhl Reports 13 (6) (2023)
Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner
Towards understanding and mitigating unintended biases in language model-driven conversational recommendation. Inf. Process. Manag. 60 (1) (2023)
Yudong Xu, Elias B. Khalil, Scott Sanner
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus. AAAI (2023)
Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias B. Khalil
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations. CoRR (2023)
Haochen Zhang, Anton Korikov, Parsa Farinneya, Mohammad Mahdi Abdollah Pour, Manasa Bharadwaj, Ali Pesaranghader, Xi Yu Huang, Yi Xin Lok, Zhaoqi Wang, Nathan Jones, Scott Sanner
Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval. SIGIR (2023)
Mohamed Reda Bouadjenek, Scott Sanner, Ga Wu
A User-Centric Analysis of Social Media for Stock Market Prediction. ACM Trans. Web 17 (2) (2023)
Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang, Scott Sanner
LogicRec: Recommendation with Users' Logical Requirements. SIGIR (2023)
Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. CoRR (2023)
Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. RecSys (2023)
Ayal Taitler, Michael Gimelfarb, Sriram Gopalakrishnan, Xiaotian Liu, Scott Sanner
pyRDDLGym: From RDDL to Gym Environments. CoRR (2022)
Xiaoyu Wang, Scott Sanner, Baher Abdulhai
A Critical Review of Traffic Signal Control and A Novel Unified View of Reinforcement Learning and Model Predictive Control Approaches for Adaptive Traffic Signal Control. CoRR (2022)
Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith
Learning to Follow Instructions in Text-Based Games. NeurIPS (2022)
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner
Online continual learning in image classification: An empirical survey. Neurocomputing 469 (2022)
Mohamed Reda Bouadjenek, Scott Sanner, Zahra Iman, Lexing Xie, Daniel Xiaoliang Shi
A longitudinal study of topic classification on Twitter. PeerJ Comput. Sci. 8 (2022)
Zhaolin Gao, Tianshu Shen, Zheda Mai, Mohamed Reda Bouadjenek, Isaac Waller, Ashton Anderson, Ron Bodkin, Scott Sanner
Mitigating the Filter Bubble While Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems. SIGIR (2022)
Noah Patton, Jihwan Jeong, Mike Gimelfarb, Scott Sanner
A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs. AAAI (2022)
Jihwan Jeong, Parth Jaggi, Andrew Butler, Scott Sanner
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming. ICML (2022)
Ruiwen Li, Zheda Mai, Chiheb Trabelsi, Zhibo Zhang, Jongseong Jang, Scott Sanner
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation. CoRR (2022)
Riley Moher, Michael Gruninger, Scott Sanner
What's in a (Data) Type? Meaningful Type Safety for Data Science. RCIS (2022)
Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith
Learning to Follow Instructions in Text-Based Games. CoRR (2022)
Siow Meng Low, Akshat Kumar, Scott Sanner
Sample-efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. CoRR (2022)
Tianshu Shen, Zheda Mai, Ga Wu, Scott Sanner
Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. WWW (2022)
Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. CoRR (2022)
Siow Meng Low, Akshat Kumar, Scott Sanner
Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. AAAI (2022)
Yudong Xu, Elias B. Khalil, Scott Sanner
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus. CoRR (2022)
Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner
Unintended Bias in Language Model-driven Conversational Recommendation. CoRR (2022)
Ga Wu, Justin Domke, Scott Sanner
Arbitrary conditional inference in variational autoencoders via fast prior network training. Mach. Learn. 111 (7) (2022)
Zhibo Zhang, Jongseong Jang, Chiheb Trabelsi, Ruiwen Li, Scott Sanner, Yeonjeong Jeong, Dongsub Shim
ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification. CoRR (2021)
Shengnan Lyu, Arpit Rana, Scott Sanner, Mohamed Reda Bouadjenek
A Workflow Analysis of Context-driven Conversational Recommendation. WWW (2021)
Michael Gimelfarb, André Barreto, Scott Sanner, Chi-Guhn Lee
Risk-Aware Transfer in Reinforcement Learning using Successor Features. NeurIPS (2021)
Ruiwen Li, Zhibo Zhang, Jiani Li, Scott Sanner, Jongseong Jang, Yeonjeong Jeong, Dongsub Shim
EDDA: Explanation-driven Data Augmentation to Improve Model and Explanation Alignment. CoRR (2021)
Hojin Yang, Tianshu Shen, Scott Sanner
Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems. SIGIR (2021)
Yew Meng Khaw, Amir Abiri Jahromi, Mohammadreza Fakhari Moghaddam Arani, Scott Sanner, Deepa Kundur, Marthe Kassouf
A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays. IEEE Trans. Smart Grid 12 (3) (2021)
Buser Say, Scott Sanner, Jo Devriendt, Jakob Nordström, Peter J. Stuckey
Planning with Learned Binarized Neural Networks Benchmarks for MaxSAT Evaluation 2021. CoRR (2021)
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
Contextual policy transfer in reinforcement learning domains via deep mixtures-of-experts. UAI (2021)
Yi Sui, Ga Wu, Scott Sanner
Multi-axis Attentive Prediction for Sparse EventData: An Application to Crime Prediction. CoRR (2021)
Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. CVPR Workshops (2021)
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner
Online Continual Learning in Image Classification: An Empirical Survey. CoRR (2021)
Yi Sui, Ga Wu, Scott Sanner
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models. NeurIPS (2021)
Mike Gimelfarb, Scott Sanner, Chi-Guhn Lee
Bayesian Experience Reuse for Learning from Multiple Demonstrators. IJCAI (2021)
Michael Gimelfarb, André Barreto, Scott Sanner, Chi-Guhn Lee
Risk-Aware Transfer in Reinforcement Learning using Successor Features. CoRR (2021)
Jihwan Jeong, Parth Jaggi, Scott Sanner
Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions. IJCAI (2021)
Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang
Online Class-Incremental Continual Learning with Adversarial Shapley Value. AAAI (2021)
Ta Jiun Ting, Xiaocan Li, Scott Sanner, Baher Abdulhai
Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction. ITSC (2021)
Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. CoRR (2021)
Parth Jaggi, Xiaoyu Wang, Nicolas Carrara, Scott Sanner, Baher Abdulhai
Microscopic Model-Based RL Approaches for Traffic Signal Control Generalize Better than Model-Free RL Approaches. ITSC (2021)
Hojin Yang, Scott Sanner, Ga Wu, Jin Peng Zhou
Bayesian Preference Elicitation with Keyphrase-Item Coembeddings for Interactive Recommendation. UMAP (2021)
Noah Patton, Jihwan Jeong, Michael Gimelfarb, Scott Sanner
RAPTOR: End-to-end Risk-Aware MDP Planning and Policy Learning by Backpropagation. CoRR (2021)
Dusan Sovilj, Paul Budnarain, Scott Sanner, Geoff Salmon, Mohan Rao
A comparative evaluation of unsupervised deep architectures for intrusion detection in sequential data streams. Expert Syst. Appl. 159 (2020)
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
Contextual Policy Reuse using Deep Mixture Models. CoRR (2020)
Bohan Zhang, Scott Sanner, Mohamed Reda Bouadjenek, Shagun Gupta
Bayesian Networks for Data Integration in the Absence of Foreign Keys. IEEE Trans. Knowl. Data Eng. 32 (4) (2020)
Buser Say, Scott Sanner
Compact and efficient encodings for planning in factored state and action spaces with learned Binarized Neural Network transition models. Artif. Intell. 285 (2020)
Zheda Mai, Ga Wu, Kai Luo, Scott Sanner
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. CoRR (2020)
Hanze Li, Scott Sanner, Kai Luo, Ga Wu
A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender Systems. RecSys (2020)
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
Bayesian Experience Reuse for Learning from Multiple Demonstrators. CoRR (2020)
Zheda Mai, Dongsub Shim, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang
Adversarial Shapley Value Experience Replay for Task-Free Continual Learning. CoRR (2020)
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
ε-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning. CoRR (2020)
Ga Wu, Buser Say, Scott Sanner
Scalable Planning with Deep Neural Network Learned Transition Models. J. Artif. Intell. Res. 68 (2020)
Mohamed Reda Bouadjenek, Scott Sanner, Yihao Du
Relevance- and interface-driven clustering for visual information retrieval. Inf. Syst. 94 (2020)
Zheda Mai, Ga Wu, Kai Luo, Scott Sanner
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. ICDM (Workshops) (2020)
Jin Peng Zhou, Ga Wu, Zheda Mai, Scott Sanner
Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering. CoRR (2020)
Zheda Mai, Hyunwoo Kim, Jihwan Jeong, Scott Sanner
Batch-level Experience Replay with Review for Continual Learning. CoRR (2020)
Kai Luo, Hojin Yang, Ga Wu, Scott Sanner
Deep Critiquing for VAE-based Recommender Systems. SIGIR (2020)
Kai Luo, Scott Sanner, Ga Wu, Hanze Li, Hojin Yang
Latent Linear Critiquing for Conversational Recommender Systems. WWW (2020)
Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner, Himanshu Rai
Noise Contrastive Estimation for One-Class Collaborative Filtering. SIGIR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Scott Sanner