David Evans
21 papers · 2003–2026 · 9 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (42) 🏃 Academic Marathon · Ultra 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Topic Evolution
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Keyword Collector
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Trend Setter
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Renaissance Researcher
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Century Club · Bronze
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Unstoppable · Bronze
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The Questioner
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Top co-authors
Research topics
Machine Learning
(19)
Artificial Intelligence
(12)
Learning Types · Machine Learning
(11)
Application Areas
(10)
Core AI
(9)
Deep Learning
(8)
Optimization & Theory
(7)
Learning Types · Deep Learning
(6)
Core Methods
(5)
Security & Privacy
(3)
Learning Paradigms
(3)
Data Science & Analytics
(2)
Methods
(2)
Models
(2)
Privacy
(2)
Keywords
adversarial example
(5)
adversarial robustness
(4)
intrinsic robustness
(4)
adversarial attack
(3)
differential privacy
(3)
large language model
(3)
natural language inference
(2)
adversarial learning
(2)
gender bia
(2)
poisoning attack
(2)
paraphrase identification
(2)
concentration measure
(2)
certified robustness
(1)
representation learning
(1)
stochastic gradient descent
(1)
causal inference
(1)
federated learning
(1)
reinforcement learning
(1)
binary classification
(1)
contrastive learning
(1)
Papers
Inferring Events from Time Series using Language Models
ACL 2026
Do Prevalent Bias Metrics Capture Allocational Harms from LLMs?
NAACL 2025
Unsupervised Concept Vector Extraction for Bias Control in LLMs
EMNLP 2025
Addressing Both Statistical and Causal Gender Fairness in NLP Models
NAACL 2024
Efficient Privacy-Preserving Stochastic Nonconvex Optimization
UAI 2023
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
NeurIPS 2023
Manipulating Transfer Learning for Property Inference
CVPR 2023
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?
NeurIPS 2023
An Empirical Analysis of Memorization in Fine-tuned Autoregressive Language Models
EMNLP 2022
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models
EMNLP 2022
Understanding Intrinsic Robustness Using Label Uncertainty
ICLR 2022
Improved Estimation of Concentration Under ℓ_p-Norm Distance Metrics Using Half Spaces
ICLR 2021
Model-Targeted Poisoning Attacks with Provable Convergence
ICML 2021
Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory
EMNLP 2020
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
ICML 2020
Pointwise Paraphrase Appraisal is Potentially Problematic
ACL 2020
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models
AISTATS 2020
Cost-Sensitive Robustness against Adversarial Examples
ICLR 2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
NeurIPS 2019
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization
NeurIPS 2018
Columbia’s Newsblaster: New Features and Future Directions
NAACL 2003