| 2026 | AAAI | Preference Optimization via Contrastive Divergence: Your Policy Is Secretly an NLL Estimator. | Zhuotong Chen, Fang Liu, Xuan Zhu, Haozhu Wang, Jiayu Li, Yanjun Qi, Mohammad Ghavamzadeh |
| 2026 | EACL | The Subtle Art of Defection: Understanding Uncooperative Behaviors in LLM based Multi-Agent Systems. | Devang Kulshreshtha, Wanyu Du, Raghav Jain, Srikanth Doss, Hang Su, Sandesh Swamy, Yanjun Qi |
| 2025 | ACL | AIDE: Attribute-Guided MultI-Hop Data Expansion for Data Scarcity in Task-Specific Fine-tuning. | Jiayu Li, Jennifer Zhu, Fang Liu, Yanjun Qi |
| 2025 | EMNLP | Zero-knowledge LLM hallucination detection and mitigation through fine-grained cross-model consistency. | Aman Goel, Daniel Schwartz, Yanjun Qi |
| 2025 | EMNLP | Graph of Attacks with Pruning: Optimizing Stealthy Jailbreak Prompt Generation for Enhanced LLM Content Moderation. | Daniel Schwartz, Dmitriy Bespalov, Zhe Wang, Ninad Kulkarni, Yanjun Qi |
| 2025 | NAACL | TurboFuzzLLM: Turbocharging Mutation-based Fuzzing for Effectively Jailbreaking Large Language Models in Practice. | Aman Goel, Xian Carrie Wu, Zhe Wang, Dmitriy Bespalov, Yanjun Qi |
| 2025 | NAACL | Augmented Adversarial Trigger Learning. | Zhe Wang, Yanjun Qi |
| 2025 | NAACL | TaeBench: Improving Quality of Toxic Adversarial Examples. | Xuan Zhu, Dmitriy Bespalov, Liwen You, Ninad Kulkarni, Yanjun Qi |
| 2025 | WWW | Hierarchical Prompt Decision Transformer: Improving Few-Shot Policy Generalization with Global and Adaptive Guidance. | Zhe Wang, Haozhu Wang, Yanjun Qi |
| 2024 | EMNLP | LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning. | Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, Yanjun Qi |
| 2024 | JSSPP | Launchpad: Learning to Schedule Using Offline and Online RL Methods. | Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi |
| 2024 | NAACL | Less is More for Improving Automatic Evaluation of Factual Consistency. | Tong Wang, Ninad Kulkarni, Yanjun Qi |
| 2023 | AAAI | Improving Interpretability via Explicit Word Interaction Graph Layer. | Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi |
| 2023 | ACL | Towards Building a Robust Toxicity Predictor. | Dmitriy Bespalov, Sourav Bhabesh, Yi Xiang, Liutong Zhou, Yanjun Qi |
| 2023 | CVPR | Estimating and Maximizing Mutual Information for Knowledge Distillation. | Aman Shrivastava, Yanjun Qi, Vicente Ordonez |
| 2023 | ICLR | PGrad: Learning Principal Gradients For Domain Generalization. | Zhe Wang, Jake Grigsby, Yanjun Qi |
| 2022 | AISTATS | Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge. | Arshdeep Sekhon, Zhe Wang, Yanjun Qi |
| 2022 | JSSPP | RARE: Renewable Energy Aware Resource Management in Datacenters. | Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi |
| 2022 | NAACL | White-box Testing of NLP models with Mask Neuron Coverage. | Arshdeep Sekhon, Yangfeng Ji, Matthew B. Dwyer, Yanjun Qi |
| 2022 | UAI | ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning. | Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi |
| 2021 | AAAI | Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning. | Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, Vicente Ordonez |
| 2021 | BMVC | Evolving Image Compositions for Feature Representation Learning. | Paola Cascante-Bonilla, Arshdeep Sekhon, Yanjun Qi, Vicente Ordonez |
| 2021 | CVPR | General Multi-Label Image Classification With Transformers. | Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi |
| 2021 | EMNLP | Towards Improving Adversarial Training of NLP Models. | Jin Yong Yoo, Yanjun Qi |
| 2020 | EMNLP | Reevaluating Adversarial Examples in Natural Language. | John X. Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, Yanjun Qi |
| 2020 | EMNLP | TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP. | John X. Morris, Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, Yanjun Qi |
| 2018 | AISTATS | Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. | Beilun Wang, Arshdeep Sekhon, Yanjun Qi |
| 2018 | ICML | A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. | Beilun Wang, Arshdeep Sekhon, Yanjun Qi |
| 2018 | NDSS | Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks. | Weilin Xu, David Evans, Yanjun Qi |
| 2018 | SP | Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. | Ji Gao, Jack Lanchantin, Mary Lou Soffa, Yanjun Qi |
| 2017 | AISTATS | A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. | Beilun Wang, Ji Gao, Yanjun Qi |
| 2017 | ICLR | DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. | Ji Gao, Beilun Wang, Zeming Lin, Weilin Xu, Yanjun Qi |
| 2017 | ICLR | Memory Matching Networks for Genomic Sequence Classification. | Jack Lanchantin, Ritambhara Singh, Yanjun Qi |
| 2017 | ICLR | A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples. | Beilun Wang, Ji Gao, Yanjun Qi |
| 2017 | PSB | Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. | Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi |
| 2017 | VizSec | Adversarial-Playground: A visualization suite showing how adversarial examples fool deep learning. | Andrew P. Norton, Yanjun Qi |
| 2016 | AAAI | MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction. | Zeming Lin, Jack Lanchantin, Yanjun Qi |
| 2016 | NDSS | Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers. | Weilin Xu, Yanjun Qi, David Evans |
| 2015 | CIKM | MAPer: A Multi-scale Adaptive Personalized Model for Temporal Human Behavior Prediction. | Sarah Masud Preum, John A. Stankovic, Yanjun Qi |
| 2015 | BSN | Causal analysis of inertial body sensors for enhancing gait assessment separability towards multiple sclerosis diagnosis. | Jiaqi Gong, John C. Lach, Yanjun Qi, Myla D. Goldman |
| 2015 | PSB | Refining Literature Curated Protein Interactions Using Expert Opinions. | znur Tastan, Yanjun Qi, Jaime G. Carbonell, Judith Klein-Seetharaman |
| 2014 | ECIR | Deep Learning for Character-Based Information Extraction. | Yanjun Qi, Sujatha G. Das, Ronan Collobert, Jason Weston |
| 2014 | PSB | An Integrated Approach To Blood-Based Cancer Diagnosis And Biomarker Discovery. | Martin Renqiang Min, Salim A. Chowdhury, Yanjun Qi, Alex Stewart, Rachel Ostroff |
| 2014 | SDM | Extracting Researcher Metadata with Labeled Features. | Sujatha Das Gollapalli, Yanjun Qi, Prasenjit Mitra, C. Lee Giles |
| 2014 | SDM | Unsupervised Feature Learning by Deep Sparse Coding. | Yunlong He, Koray Kavukcuoglu, Yun Wang, Arthur Szlam, Yanjun Qi |
| 2014 | UCC | Comprehensive Elastic Resource Management to Ensure Predictable Performance for Scientific Applications on Public IaaS Clouds. | In Kee Kim, Jacob Steele, Yanjun Qi, Marty Humphrey |
| 2012 | ICPR | Large-scale image classification using supervised spatial encoder. | Dmitriy Bespalov, Yanjun Qi, Bing Bai, Ali Shokoufandeh |
| 2012 | PSB | Determining Confidence of Predicted Interactions Between HIV-1 and Human Proteins Using Conformal Method. | Ilia Nouretdinov, Alex Gammerman, Yanjun Qi, Judith Klein-Seetharaman |
| 2011 | CIKM | Sentiment classification based on supervised latent n-gram analysis. | Dmitriy Bespalov, Bing Bai, Yanjun Qi, Ali Shokoufandeh |
| 2011 | SDM | Sparse Latent Semantic Analysis. | Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell |
| 2011 | SDM | Semi-Supervised Convolution Graph Kernels for Relation Extraction. | Xia Ning, Yanjun Qi |
| 2010 | ICDM | Learning Preferences with Millions of Parameters by Enforcing Sparsity. | Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell |
| 2010 | SDM | Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning. | Pavel P. Kuksa, Yanjun Qi |
| 2009 | CIKM | Supervised semantic indexing. | Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger |
| 2009 | CIKM | Combining labeled and unlabeled data with word-class distribution learning. | Yanjun Qi, Ronan Collobert, Pavel P. Kuksa, Koray Kavukcuoglu, Jason Weston |
| 2009 | ICDM | Semi-Supervised Sequence Labeling with Self-Learned Features. | Yanjun Qi, Pavel P. Kuksa, Ronan Collobert, Kunihiko Sadamasa, Koray Kavukcuoglu, Jason Weston |
| 2009 | PSB | Prediction of Interactions Between HIV-1 and Human Proteins by Information Integration. | znur Tastan, Yanjun Qi, Jaime G. Carbonell, Judith Klein-Seetharaman |
| 2008 | ISMB | Protein complex identification by supervised graph local clustering. | Yanjun Qi, Fernanda Balem, Christos Faloutsos, Judith Klein-Seetharaman, Ziv Bar-Joseph |
| 2005 | PSB | Random Forest Similarity for Protein-Protein Interaction Prediction from Multiple Sources. | Yanjun Qi, Judith Klein-Seetharaman, Ziv Bar-Joseph |
| 2002 | ICPR | A Probabilistic Model for Camera Zoom Detection. | Rong Jin, Yanjun Qi, Alexander G. Hauptmann |