← Authors

Zachary Lipton

43 papers · 2018–2024 · 9 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (6) 🌍 Conference Polyglot (9) 🌈 Renaissance Researcher (10) 🐝 Cross-Pollinator (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (12) πŸ† Keyword Champion (5) ⚑ Prolific Year (6) ❓ The Questioner (3) πŸ—ƒοΈ Keyword Collector (214) πŸ“ˆ Trend Setter πŸ’Ž Century Club (43) πŸ”₯ Unstoppable (7)

Conferences

NIPS (18) ICML (9) AISTATS (5) EACL (3) EMNLP (3) ACL (2) ALT (1) ICLR (1) UAI (1)

Top co-authors

Saurabh Garg (11) Sivaraman Balakrishnan (8) Liu Leqi (5) Kamyar Azizzadenesheli (4) Audrey Huang (4) Yifan Wu (4) Divyansh Kaushik (3) Kundan Krishna (3) Sanjana Ramprasad (3) Mrigank Raman (2)

Keywords

domain adaptation (11) distribution shift (7) label shift (5) causal inference (4) neural network (4) unsupervised learning (3) generalization bound (2) convolutional neural network (2) empirical risk minimization (2) sample complexity (2) markov decision process (2) off-policy evaluation (2) semi-supervised learning (2) image classification (2) adversarial robustness (2) transfer learning (2) text summarization (2) algorithmic fairness (2) representation learning (2) covariate shift (2)

Papers

Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains EACL 2024
Analyzing LLM Behavior in Dialogue Summarization: Unveiling Circumstantial Hallucination Trends ACL 2024
Post-Hoc Reversal: Are We Selecting Models Prematurely? NIPS 2024
A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning NIPS 2024
Goodhart’s Law Applies to NLP’s Explanation Benchmarks EACL 2024
The Future of Web Data Mining: Insights from Multimodal and Code-based Extraction Methods EACL 2024
Auditing Fairness under Unobserved Confounding AISTATS 2024
Timing as an Action: Learning When to Observe and Act AISTATS 2024
Partially Interpretable Models with Guarantees on Coverage and Accuracy ALT 2024
Domain Adaptation under Missingness Shift AISTATS 2023
Risk-limiting financial audits via weighted sampling without replacement UAI 2023
USB: A Unified Summarization Benchmark Across Tasks and Domains EMNLP 2023
Model-tuning Via Prompts Makes NLP Models Adversarially Robust EMNLP 2023
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift NIPS 2023
Deep Equilibrium Based Neural Operators for Steady-State PDEs NIPS 2023
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms NIPS 2023
Downstream Datasets Make Surprisingly Good Pretraining Corpora ACL 2023
Domain Adaptation under Open Set Label Shift NIPS 2022
Supervised Learning with General Risk Functionals ICML 2022
Unsupervised Learning under Latent Label Shift NIPS 2022
Practical Benefits of Feature Feedback Under Distribution Shift EMNLP 2022
Off-Policy Risk Assessment for Markov Decision Processes AISTATS 2022
Characterizing Datapoints via Second-Split Forgetting NIPS 2022
Rebounding Bandits for Modeling Satiation Effects NIPS 2021
Mixture Proportion Estimation and PU Learning:A Modern Approach NIPS 2021
Parametric Complexity Bounds for Approximating PDEs with Neural Networks NIPS 2021
Efficient Online Estimation of Causal Effects by Deciding What to Observe NIPS 2021
Off-Policy Risk Assessment in Contextual Bandits NIPS 2021
Causal Inference with Selectively Deconfounded Data AISTATS 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization ICML 2021
On Proximal Policy Optimization’s Heavy-tailed Gradients ICML 2021
Correcting Exposure Bias for Link Recommendation ICML 2021
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data ICLR 2020
Uncertainty-Aware Lookahead Factor Models for Quantitative Investing ICML 2020
A Unified View of Label Shift Estimation NIPS 2020
What is the Effect of Importance Weighting in Deep Learning? ICML 2019
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment ICML 2019
Game Design for Eliciting Distinguishable Behavior NIPS 2019
Learning Robust Global Representations by Penalizing Local Predictive Power NIPS 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift NIPS 2019
Does mitigating ML's impact disparity require treatment disparity? NIPS 2018
Born Again Neural Networks ICML 2018
Detecting and Correcting for Label Shift with Black Box Predictors ICML 2018