Liang, Percy

Concept Bottleneck Models

Koh, P. W., Nguyen, T., Tang, Y. S., Mussmann, S., Pierson, E., Kim, B., & Liang, P. (2020) · arXiv

Explainable Artificial Intelligence (XAI)Machine Learning in Healthcare

Cited by 338

Traversing Knowledge Graphs in Vector Space

Guu, K., Miller, J., & Liang, P. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

Advanced Graph Neural NetworksTopic Modeling

Cited by 319

Generating Sentences by Editing Prototypes

Guu, K., Hashimoto, T. B., Oren, Y., & Liang, P. (2018) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 300

Prefix-Tuning: Optimizing Continuous Prompts for Generation

Li, X. L., & Liang, P. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 289

Holistic Evaluation of Language Models

Liang, P., Bommasani, R., Lee, T., Tsipras, D., Soylu, D., Yasunaga, M., Zhang, Y., Narayanan, D., Wu, Y., Kumar, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 255

Social Simulacra: Creating Populated Prototypes for Social Computing Systems

Park, J. S., Popowski, L., Cai, C., Morris, M. R., Liang, P., & Bernstein, M. S. (2022) · Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 212

Stronger Data Poisoning Attacks Break Data Sanitization Defenses

Koh, P. W., Steinhardt, J., & Liang, P. (2018) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 189

Unifying Human and Statistical Evaluation for Natural Language Generation

Hashimoto, T. B., Zhang, H., & Liang, P. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 161

Evaluating Verifiability in Generative Search Engines

Liu, N. F., Zhang, T., & Liang, P. (2023) · arXiv

Information Retrieval and Search BehaviorMisinformation and Its Impacts

Cited by 143

Evaluating Verifiability in Generative Search Engines

Liu, N., Zhang, T., & Liang, P. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Information Retrieval and Search BehaviorMisinformation and Its Impacts

Cited by 143

An Explanation of In-context Learning as Implicit Bayesian Inference

Xie, S. M., Raghunathan, A., Liang, P., & Ma, T. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 138

Learning Language Games through Interaction

Wang, S. I., Liang, P., & Manning, C. D. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 132

Decoupling Strategy and Generation in Negotiation Dialogues

He, H., Chen, D., Balakrishnan, A., & Liang, P. (2018) · arXiv

Multi-Agent Systems and NegotiationSpeech and dialogue systems

Cited by 130

A Retrieve-and-Edit Framework for Predicting Structured Outputs

Hashimoto, T. B., Guu, K., Oren, Y., & Liang, P. (2018) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 126

Whose Opinions Do Language Models Reflect?

Santurkar, S., Durmus, E., Ladhak, F., Lee, C., Liang, P., & Hashimoto, T. (2023) · arXiv

Sentiment Analysis and Opinion MiningEthics and Social Impacts of AI

Cited by 114

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Garg, S., Tsipras, D., Liang, P., & Valiant, G. (2022) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 110

Designing and Interpreting Probes with Control Tasks

Hewitt, J., & Liang, P. (2019) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 110

On the Societal Impact of Open Foundation Models

Kapoor, S., Bommasani, R., Klyman, K., Longpre, S., Ramaswami, A., Cihon, P., Hopkins, A., Bankston, K., Biderman, S., Bogen, M., et al. (2024) · arXiv

Ethics and Social Impacts of AILaw, AI, and Intellectual Property

Cited by 103

SPoC: Search-based Pseudocode to Code

Kulal, S., Pasupat, P., Chandra, K., Lee, M., Padon, O., Aiken, A., & Liang, P. (2019) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 103

Task-Oriented Dialogue as Dataflow Synthesis

Andreas, J., Bufe, J., Burkett, D., Chen, C., Clausman, J., Crawford, J., Crim, K., DeLoach, J., Dorner, L., Eisner, J., et al. (2020) · Transactions of the Association for Computational Linguistics

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 98

The price of debiasing automatic metrics in natural language evalaution

Chaganty, A., Mussmann, S., & Liang, P. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 96

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU

Sheng, Y., Zheng, L., Yuan, B., Li, Z., Ryabinin, M., Fu, D. Y., Xie, Z., Chen, B., Barrett, C., Gonzalez, J. E., et al. (2023) · arXiv

Parallel Computing and Optimization TechniquesNatural Language Processing Techniques

Cited by 86

Graph-based, Self-Supervised Program Repair from Diagnostic Feedback

Yasunaga, M., & Liang, P. (2020) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 81

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback

Dubois, Y., Li, X., Taori, R., Zhang, T., Gulrajani, I., Ba, J., Guestrin, C., Liang, P., & Hashimoto, T. B. (2023) · arXiv

Reinforcement Learning in RoboticsSimulation Techniques and Applications

Cited by 78