Percy Liang

Q: What Schools Are Affiliated With Percy Liang

Percy Liang is affiliated with the following schools: University of California, Berkeley, Stanford University

Percy Liang's AcademicInfluence.com Rankings

Percy Liang

Computer Science

#3077

World Rank

#3227

Historical Rank

Database

#593

World Rank

#622

Historical Rank

computer-science Degrees

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Computer Science

Percy Liang's Degrees

PhD Computer Science University of California, Berkeley
Bachelors Computer Science Stanford University

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Percy Liang's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

SQuAD: 100,000+ Questions for Machine Comprehension of Text (2016) (5372)
Understanding Black-box Predictions via Influence Functions (2017) (1897)
Know What You Don’t Know: Unanswerable Questions for SQuAD (2018) (1786)
Semantic Parsing on Freebase from Question-Answer Pairs (2013) (1515)
Adversarial Examples for Evaluating Reading Comprehension Systems (2017) (1254)
Prefix-Tuning: Optimizing Continuous Prompts for Generation (2021) (986)
On the Opportunities and Risks of Foundation Models (2021) (938)
Certified Defenses against Adversarial Examples (2018) (805)
Strategies for Pre-training Graph Neural Networks (2019) (621)
Learning Dependency-Based Compositional Semantics (2011) (590)
WILDS: A Benchmark of in-the-Wild Distribution Shifts (2020) (559)
QuAC: Question Answering in Context (2018) (548)
Dropout Training as Adaptive Regularization (2013) (539)
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization (2019) (529)
Certified Defenses for Data Poisoning Attacks (2017) (524)
Unlabeled Data Improves Adversarial Robustness (2019) (522)
Semantic Parsing via Paraphrasing (2014) (514)
Alignment by Agreement (2006) (509)
Compositional Semantic Parsing on Semi-Structured Tables (2015) (458)
Data Recombination for Neural Semantic Parsing (2016) (420)
Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer (2018) (417)
Semi-Supervised Learning for Natural Language (2005) (366)
Fairness Without Demographics in Repeated Loss Minimization (2018) (360)
Semidefinite relaxations for certifying robustness to adversarial examples (2018) (359)
Learning Bilingual Lexicons from Monolingual Corpora (2008) (351)
Designing and Interpreting Probes with Control Tasks (2019) (347)
Traversing Knowledge Graphs in Vector Space (2015) (325)
An End-to-End Discriminative Approach to Machine Translation (2006) (321)
Learning Semantic Correspondences with Less Supervision (2009) (320)
Learning a SAT Solver from Single-Bit Supervision (2018) (316)
Building a Semantic Parser Overnight (2015) (313)
Generating Sentences by Editing Prototypes (2017) (265)
Emergent Abilities of Large Language Models (2022) (260)
Concept Bottleneck Models (2020) (245)
Online EM for Unsupervised Models (2009) (226)
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) (218)
Distributionally Robust Neural Networks (2020) (214)
The Infinite PCFG Using Hierarchical Dirichlet Processes (2007) (213)
A Simple Domain-Independent Probabilistic Approach to Generation (2010) (212)
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics (2017) (201)
Verified Uncertainty Calibration (2019) (199)
Certified Robustness to Adversarial Word Substitutions (2019) (195)
An Investigation of Why Overparameterization Exacerbates Spurious Correlations (2020) (189)
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering (2021) (187)
From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood (2017) (175)
Adversarial Training Can Hurt Generalization (2019) (172)
Learning Language Games through Interaction (2016) (168)
Just Train Twice: Improving Group Robustness without Training Group Information (2021) (168)
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings (2017) (164)
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution (2022) (164)
Unifying Human and Statistical Evaluation for Natural Language Generation (2019) (158)
A Game-Theoretic Approach to Generating Spatial Descriptions (2010) (152)
Synthesizing program input grammars (2016) (145)
Stronger data poisoning attacks break data sanitization defenses (2018) (144)
An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators (2008) (139)
A Data Driven Approach for Algebraic Loop Invariants (2013) (133)
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy (2020) (132)
Spectral Experts for Estimating Mixtures of Linear Regressions (2013) (131)
Lambda Dependency-Based Compositional Semantics (2013) (128)
Training Classifiers with Natural Language Explanations (2018) (128)
A Retrieve-and-Edit Framework for Predicting Structured Outputs (2018) (127)
Learning from measurements in exponential families (2009) (126)
Learning executable semantic parsers for natural language understanding (2016) (123)
Enabling Language Models to Fill in the Blanks (2020) (122)
Understanding Self-Training for Gradual Domain Adaptation (2020) (117)
Learning Programs: A Hierarchical Bayesian Approach (2010) (117)
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization (2021) (113)
Diffusion-LM Improves Controllable Text Generation (2022) (112)
On the Accuracy of Influence Functions for Measuring Group Effects (2019) (110)
Selection Via Proxy: Efficient Data Selection For Deep Learning (2019) (104)
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback (2020) (102)
Distributionally Robust Language Modeling (2019) (100)
Transforming Question Answering Datasets Into Natural Language Inference Datasets (2018) (97)
Calibrated Structured Prediction (2015) (96)
Selective Question Answering under Domain Shift (2020) (94)
Large Language Models Can Be Strong Differentially Private Learners (2021) (94)
Linking People in Videos with "Their" Names Using Coreference Resolution (2014) (93)
Task-Oriented Dialogue as Dataflow Synthesis (2020) (92)
Simpler Context-Dependent Logical Forms via Model Projections (2016) (90)
Decoupling Strategy and Generation in Negotiation Dialogues (2018) (88)
The price of debiasing automatic metrics in natural language evalaution (2018) (86)
An Explanation of In-context Learning as Implicit Bayesian Inference (2021) (81)
Imitation Learning of Agenda-based Semantic Parsers (2015) (81)
Structure compilation: trading structure for features (2008) (79)
Holistic Evaluation of Language Models (2022) (79)
Tensor Factorization via Matrix Factorization (2015) (76)
Robust Encodings: A Framework for Combating Adversarial Typos (2020) (74)
Bringing Machine Learning and Compositional Semantics Together (2015) (71)
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming (2020) (69)
Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm (2014) (68)
SPoC: Search-based Pseudocode to Code (2019) (67)
Naturalizing a Programming Language via Interactive Learning (2017) (65)
CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities (2022) (63)
Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases (2020) (60)
Convexified Convolutional Neural Networks (2016) (59)
Video Event Understanding Using Natural Language Descriptions (2013) (57)
LinkBERT: Pretraining Language Models with Document Links (2022) (57)
A Probabilistic Approach to Diachronic Phonology (2007) (56)
Environment-Driven Lexicon Induction for High-Level Instructions (2015) (56)
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration (2018) (55)
Inferring Logical Forms From Denotations (2016) (55)
Scaling abstraction refinement via pruning (2011) (54)
Robustness to Spurious Correlations via Human Annotations (2020) (52)
World of Bits: An Open-Domain Platform for Web-Based Agents (2017) (52)
Developing Bug-Free Machine Learning Systems With Formal Mathematics (2017) (51)
Defending against Whitebox Adversarial Attacks via Randomized Discretization (2019) (50)
Altitude Training: Strong Bounds for Single-Layer Dropout (2014) (49)
Learning minimal abstractions (2011) (47)
Pun Generation with Surprise (2019) (46)
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately (2020) (44)
Macro Grammars and Holistic Triggering for Efficient Semantic Parsing (2017) (43)
Learning nongenerative grammatical models for document analysis (2005) (42)
Type-Based MCMC (2010) (42)
Break-It-Fix-It: Unsupervised Learning for Program Repair (2021) (41)
Pre-training Graph Neural Networks (2019) (40)
FrAngel: component-based synthesis with control structures (2018) (40)
Identifiability and Unmixing of Latent Parse Trees (2012) (39)
Agreement-Based Learning (2007) (38)
Zero-shot Entity Extraction from Web Pages (2014) (38)
Extending the WILDS Benchmark for Unsupervised Adaptation (2021) (37)
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes (2022) (36)
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness (2020) (36)
Shaping Visual Representations with Language for Few-Shot Classification (2019) (34)
ExpBERT: Representation Engineering with Natural Language Explanations (2020) (34)
Estimating Latent-Variable Graphical Models using Moments and Likelihoods (2014) (33)
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices (2020) (32)
Analyzing the Errors of Unsupervised Learning (2008) (32)
Codified audio language modeling learns useful representations for music information retrieval (2021) (31)
Mapping natural language commands to web elements (2018) (28)
The EOS Decision and Length Extrapolation (2020) (27)
GreaseLM: Graph REASoning Enhanced Language Models for Question Answering (2022) (27)
Feature Noising for Log-Linear Structured Prediction (2013) (27)
A Probabilistic Approach to Language Change (2007) (26)
Unsupervised Risk Estimation Using Only Conditional Independence Structure (2016) (25)
Selective Classification Can Magnify Disparities Across Groups (2020) (24)
A dynamic evaluation of the precision of static heap abstractions (2010) (24)
Efficient geometric algorithms for parsing in two dimensions (2005) (23)
Learning Adaptive Language Interfaces through Decomposition (2020) (23)
Conditional probing: measuring usable information beyond a baseline (2021) (23)
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation (2022) (22)
RNNs Can Generate Bounded Hierarchical Languages with Optimal Memory (2020) (22)
On the Relationship between Data Efficiency and Error for Uncertainty Sampling (2018) (22)
Importance sampling for unbiased on-demand evaluation of knowledge base population (2017) (21)
Active learning of points-to specifications (2017) (21)
Prediction with a short memory (2016) (20)
On-the-Job Learning with Bayesian Decision Theory (2015) (20)
Computer-aided risk evaluation system for capital investment (1994) (20)
Learning Where to Sample in Structured Prediction (2015) (20)
Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings (2016) (19)
Asymptotically Optimal Regularization in Smooth Parametric Models (2009) (19)
A permutation-augmented sampler for DP mixture models (2007) (19)
Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches (2021) (18)
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts (2022) (18)
Learning Overcomplete HMMs (2017) (18)
Planning, Inference and Pragmatics in Sequential Language Games (2018) (17)
GreaseLM: Graph REASoning Enhanced Language Models (2022) (17)
CS229T/STAT231: Statistical Learning Theory (Winter 2016) (2015) (17)
Simple MAP Inference via Low-Rank Relaxations (2014) (17)
How Much is 131 Million Dollars? Putting Numbers in Perspective with Compositional Descriptions (2016) (16)
Textual Analogy Parsing: What’s Shared and What’s Compared among Analogous Facts (2018) (14)
Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning (2022) (14)
LM-Critic: Language Models for Unsupervised Grammatical Error Correction (2021) (13)
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP (2022) (13)
Inferring Multidimensional Rates of Aging from Cross-Sectional Data (2018) (13)
Deep Bidirectional Language-Knowledge Graph Pretraining (2022) (13)
Probabilistic grammars and hierarchical Dirichlet processes (2018) (12)
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss (2018) (12)
Ambitious Data Science Can Be Painless (2019) (12)
Social Simulacra: Creating Populated Prototypes for Social Computing Systems (2022) (12)
Benchmarking Large Language Models for News Summarization (2023) (12)
Estimation from Indirect Supervision with Linear Moments (2016) (11)
Feature Noise Induces Loss Discrepancy Across Groups (2019) (11)
Contrastive Decoding: Open-ended Text Generation as Optimization (2022) (11)
On the Interaction between Norm and Dimensionality: Multiple Regimes in Learning (2010) (10)
Unsupervised Transformation Learning via Convex Relaxations (2017) (10)
Maximum Weighted Loss Discrepancy (2019) (10)
Evaluating Human-Language Model Interaction (2022) (9)
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift (2022) (9)
Filtering with Abstract Particles (2014) (9)
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks (2020) (9)
The Statistics of Streaming Sparse Regression (2014) (9)
Learning Fast-Mixing Models for Structured Prediction (2015) (9)
Select Via Proxy: Efficient Data Selection For Training Deep Networks (2018) (9)
Decentralized Training of Foundation Models in Heterogeneous Environments (2022) (8)
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? (2022) (8)
Catformer: Designing Stable Transformers via Sensitivity Analysis (2021) (8)
Relaxations for inference in restricted Boltzmann machines (2013) (8)
LILA: Language-Informed Latent Actions (2021) (8)
Learning Autocomplete Systems as a Communication Game (2019) (8)
Improving Self-Supervised Learning by Characterizing Idealized Representations (2022) (8)
Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning (2020) (8)
Insights into Pre-training via Simpler Synthetic Tasks (2022) (8)
Retrieval-Augmented Multimodal Language Modeling (2022) (8)
Generative Agents: Interactive Simulacra of Human Behavior (2023) (6)
Estimating Mixture Models via Mixtures of Polynomials (2015) (6)
Learning with Relaxed Supervision (2015) (6)
No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets (2021) (6)
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing (2015) (5)
Percy (2019) (5)
Learning Abstract Models for Long-Horizon Exploration (2018) (5)
Data Augmentation via Levy Processes (2016) (5)
Noise Induces Loss Discrepancy Across Groups for Linear Regression (2019) (5)
Simultaneous diagonalization: the asymmetric, low-rank, and noisy settings (2015) (5)
Truncation Sampling as Language Model Desmoothing (2022) (5)
Learning Abstract Models for Strategic Exploration and Fast Reward Transfer (2020) (4)
QSRL : A Semantic Role-Labeling Schema for Quantitative Facts (2018) (4)
SHEET SAGE: LEAD SHEETS FROM MUSIC AUDIO (2021) (4)
Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization (2020) (4)
Ensembles and Cocktails: Robust Finetuning for Natural Language Generation (2021) (4)
Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality (2021) (4)
Generalized Binary Search For Split-Neighborly Problems (2018) (4)
Methods and Experiments With Bounded Tree-width Markov Networks (2004) (4)
Talking to computers in natural language (2014) (4)
Inferring Multi-Dimensional Rates of Aging from Cross-Sectional Data (2018) (4)
Reified Context Models (2015) (4)
A Dynamic Data Structure for Checking Hyperacyclicity (2005) (3)
Whose Opinions Do Language Models Reflect? (2023) (3)
Out-of-Distribution Robustness via Targeted Augmentations (2022) (3)
No, to the Right: Online Language Corrections for Robotic Manipulation via Shared Autonomy (2023) (3)
High-throughput Generative Inference of Large Language Models with a Single GPU (2023) (3)
Data Selection for Language Models via Importance Resampling (2023) (3)
How Does Contrastive Pre-training Connect Disparate Domains? (2021) (3)
Are Sample-Efficient NLP Models More Robust? (2022) (2)
A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree (2019) (2)
How Much of a Hypertree can be Captured by Windmills (2005) (1)
Evaluating Verifiability in Generative Search Engines (2023) (1)
Language-Driven Representation Learning for Robotics (2023) (1)
Trustworthy Social Bias Measurement (2022) (1)
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? (2022) (1)
Formal Methods For Probabilistic Programming (2017) (1)
Ecosystem Graphs: The Social Footprint of Foundation Models (2023) (1)
When Covariate-shifted Data Augmentation Increases Test Error And How to Fix It (2019) (1)
Computer Science and Artificial Intelligence Laboratory A Dynamic Data Structure for Checking Hyperacyclicity (2005) (1)
Data collection for a new conversational dialogue system (2017) (1)
Learning Semantic Parsers for Natural Language Understanding (2015) (1)
ROBUST DEEP SEMANTICS FOR LANGUAGE UNDERSTANDING LELAND STANFORD UNIVERSITY JUNE 2018 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED (2018) (0)
Link-BERT: Pretraining a Language Model with Document Links (2022) (0)
Melody transcription via generative pre-training (2022) (0)
Robust Deep Semantics for Language Understanding (2018) (0)
Hierarchy-Driven Exploration for Reinforcement Learning (2018) (0)
GitHub Repository for "FrAngel (2018) (0)
Overparameterization hurts worst-group accuracy with spurious correlations (2020) (0)
Out-of-Domain Robustness via Targeted Augmentations (2023) (0)
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs (2023) (0)
Evaluating Self-Supervised Learning via Risk Decomposition (2023) (0)
1 Active Learning of Points-To Specifications (2017) (0)
Foundation Models and Fair Use (2023) (0)
A Data Structure for Maintaining Acyclicity in Hypergraphs (0)
Active Learning of Points-To Specifications Osbert Bastani (2018) (0)
NEURAL NETWORKS AND THE SATISFIABILITY PROBLEM A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (2019) (0)
What Makes Representation Learning from Videos Hard for Control? (2022) (0)
Shared Autonomy for Robotic Manipulation with Language Corrections (2022) (0)
Improving Representational Continuity via Continued Pretraining (2023) (0)
DrRepair: A Self-Supervised, Graph-Attentional Approach to Repairing Programs from Diagnostic Feedback (2020) (0)
Do Question Answering Modeling Improvements Hold Across Benchmarks? (2021) (0)
LinkBERT: Language Model Pretraining with Document Link Knowledge (2022) (0)
2022 Source Labeled Unlabeled Belgium France Norway Validation China Target United States Canada UK Japan Mexico Extra (2022) (0)
Task-Agnostic Robust Encodings for Combating Adversarial Typos (2019) (0)
Simplifying Models with Unlabeled Output Data (2020) (0)

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Other Resources About Percy Liang

cs.stanford.edu

What Schools Are Affiliated With Percy Liang?

Percy Liang is affiliated with the following schools:

Percy Liang's Academic­Influence.com Rankings