Zachary Lipton

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

Achievements

+13 more ↓

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (14) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (9)

🗺️ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🤝 Dynamic Duo (11) 👑 Triple Crown 🔬 Deep Specialist (12) 🏆 Keyword Champion (5) ⚡ Prolific Year (6) ❓ The Questioner (3) 🗃️ Keyword Collector (214) 📈 Trend Setter 💎 Century Club (43) 🔥 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