- 2024-03: Five papers at NAACL on LLM security (4 main and 1 finding): two on the backdoor attack, one on backdoor defense, one on jailbreak attacks, and one on model fingerprint. Stay tuned on these exciting fields
- 2024-03: PreDa for personalized federated learning is accepted at CVPR 2024.
- 2024-01: Three papers at ICLR.
- 2024-01: Two papers at TMLR.
- 2023-12: Invited Talk at NeurIPS TDW workshop
- 2023-10: Our paper MoleculeSTM has been accepted to Nature Machine Intelligence. MoleculeSTM aims to align the nature language and molecule representation into the same representation space.
- 2023-10: Three papers at EMNLP and one paper at NeurIPS. For our NeurIPS paper, we study a new threat of the instruction tuning of LLMs by injecting the Ads. This is the first work that views the LLMs as the generative model and aims to attack the generative property of LLMs.
- 2022-10: Our tutorial on Security and Privacy in the Era of Large Language Models is accepted to NAACL.
- 2022-05: One paper at ACL. Congratulations to zhuofeng and jiazhao. We propose an attention-based method to defend against NLP backdoor attacks
- 2023-04: Two papers at ICML. Congratulations to Jiachen and Zhiyuan. We propose the first benchmark for code copyright of code generation models.
- 2023-02: Two papers at CVPR. Congratulations to Yiming and Xiaogeng. Xiaogeng is an intern from my group at ASU.
- 2023-02: I will give a tutorial at CVPR 2023 on the topic of trustworthiness in the era of Foundation Models. Stay tuned!
- Sep 13, 2021: Impact Award from Argonne National Laboratory.
- Sep 9, 2021: Our 2 papers got accepted to the Artificial Intelligence for Human-Robot Interaction (AI-HRI) at AAAI Fall Symposium Series:
- Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams
- APReL: A Library for Active Preference-based Reward Learning Algorithms
- Aug 15, 2021: We have released our Python library APReL, which unifies active preference-based reward learning algorithms.
- Aug 4, 2021: Our paper titled "Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences" got accepted to The International Journal of Robotics Research (IJRR).
- Jul 9, 2021: Our paper titled "Learning How to Dynamically Route Autonomous Vehicles on Shared Roads" got accepted to Transportation Research Part C: Emerging Technologies (TR_C).
- May 18, 2021: Our paper titled "Emergent Prosociality in Multi-Agent Games Through Gifting" got accepted to the 30th International Joint Conference on Artificial Intelligence (IJCAI).
- May 5, 2021: Our paper titled "Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy" got accepted to the IEEE Transactions on Control of Network Systems (TCNS).
- Feb 28, 2020: Our paper titled "ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes" got accepted to the 2021 International Conference on Robotics and Automation (ICRA).
- Dec 23, 2020: Our paper titled "Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic" got accepted to the 12th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS).
- Aug 12, 2020: Our paper titled "Multi-Agent Safe Planning with Gaussian Processes" got accepted to the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Jul 13, 2020: The recordings of our RSS 2020 workshop on "Emergent Behaviors in Human-Robot Systems" are available on YouTube.
- Jun 25, 2020: Check our IJRR submission about learning reward functions by optimally combining demonstration and preference data on arXiv.
- Jun 22, 2020: Our talks at RSS 2020 are available on YouTube now:
- Active Preference-Based Gaussian Process Regression for Reward Learning
- Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving
- May 6, 2020: Our 2 papers got accepted to the Robotics: Science and Systems (RSS) 2020 conference:
- Active Preference-Based Gaussian Process Regression for Reward Learning
- Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving
- Apr 7, 2020: Our paper titled "When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans" got honorable mention award at HRI 2020!
- Mar 28, 2020: Check Minae's talk at HRI 2020 on "When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans" here.
- Mar 6, 2020: We are organizing a workshop on "Emergent Behaviors in Human-Robot Systems" at RSS 2020. Check it out here for more details and the call for contributions.
- Dec 1, 2019: Our paper titled "When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans" got accepted to 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI).
- Oct 24, 2019: TechXplore compiled a story about our work "Asking Easy Questions: A User-Friendly Approach to Active Reward Learning". Check it out here.
- Sep 11, 2019: Our paper titled "Asking Easy Questions: A User-Friendly Approach to Active Reward Learning" got accepted to the Conference on Robot Learning (CoRL) 2019.
- Sep 10, 2019: Check our preprint about learning dynamic routing of autonomous cars to decrease traffic congestion on arXiv.
- Jul 19, 2019: Our paper titled "The Green Choice: Learning and Influencing Human Decisions on Shared Roads" got accepted at CDC 2019!
- Jul 18, 2019: Our paper titled "Active Learning of Reward Dynamics from Hierarchical Queries" got accepted to 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Jun 19, 2019: Check our preprint about batch-mode active learning on arXiv.
- Apr 8, 2019: Check our CDC 2019 submission about mixed-autonomy traffic on arXiv.
- Jan 27, 2019: Our paper titled "Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models" got accepted at American Control Conference 2019.
- Sep 5, 2018: Our paper titled "Altruistic Autonomy: Beating Congestion on Shared Roads" got accepted to the 13th International Workshop on the Algorithmic Foundations of Robotics (WAFR).
- Sep 1, 2018: Our paper titled "Batch Active Preference-Based Learning of Reward Functions" got accepted at Conference on Robot Learning (CoRL) 2018.
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