Michael Zhang

28 papers · 2017–2025 · 11 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (8)

🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (9) 🌉 Interdisciplinary Bridge 🌱 Topic Pioneer 🏆 Grand Slam 🤝 Dynamic Duo (10) 👑 Triple Crown 🗃️ Keyword Collector (111) ❓ The Questioner ⚡ Prolific Year (6) 🚀 Conference Pioneer 💎 Century Club (28) 🔥 Unstoppable (9) 📈 Trend Setter

Conferences

ICLR (5) NIPS (5) EMNLP (4) ICML (4) AISTATS (3) CORL (2) AAAI (1) ACL (1) MLHC (1) NAACL (1) UAI (1)

Top co-authors

Christopher Re (10) Eunsol Choi (6) Greg Durrett (3) Yasumasa Onoe (3) Simran Arora (2) Barbara Engelhardt (2) Kayvon Fatahalian (2) Shankar Padmanabhan (2) Jimmy Ba (2) Daniel Y Fu (2)

Keywords

domain generalization (4) language model (4) question answering (4) representation learning (3) contrastive learning (3) reinforcement learning (3) knowledge editing (2) foundation model (2) distributed inference (2) embedding space (2) domain adaptation (1) transfer learning (1) stochastic gradient descent (1) probabilistic modeling (1) online learning (1) knowledge distillation (1) model calibration (1) bayesian nonparametrics (1) uncertainty quantification (1) curriculum learning (1)

Papers

LoLCATs: On Low-Rank Linearizing of Large Language Models ICLR 2025 The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry ICLR 2024 Simple linear attention language models balance the recall-throughput tradeoff ICML 2024 Propagating Knowledge Updates to LMs Through Distillation NIPS 2023 Effectively Modeling Time Series with Simple Discrete State Spaces ICLR 2023 Mitigating Temporal Misalignment by Discarding Outdated Facts EMNLP 2023 Can LMs Learn New Entities from Descriptions? Challenges in Propagating Injected Knowledge ACL 2023 Selectively Answering Ambiguous Questions EMNLP 2023 Simple Hardware-Efficient Long Convolutions for Sequence Modeling ICML 2023 Shoring up the foundations: fusing model embeddings and weak supervision UAI 2022 Contrastive Adapters for Foundation Model Group Robustness NIPS 2022 Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence EMNLP 2022 Triangle and Four Cycle Counting with Predictions in Graph Streams ICLR 2022 Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning ICML 2022 Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations ICML 2022 Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity MLHC 2022 Entity Cloze By Date: What LMs Know About Unseen Entities NAACL 2022 Personalized Federated Learning with First Order Model Optimization ICLR 2021 Latent variable modeling with random features AISTATS 2021 SituatedQA: Incorporating Extra-Linguistic Contexts into QA EMNLP 2021 Learning Domain Invariant Representations in Goal-conditioned Block MDPs NIPS 2021 Soft Multicopter Control Using Neural Dynamics Identification CORL 2020 Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes AISTATS 2020 Distributed, partially collapsed MCMC for Bayesian Nonparametrics AISTATS 2020 Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions AAAI 2020 Lookahead Optimizer: k steps forward, 1 step back NIPS 2019 Communication Efficient Parallel Algorithms for Optimization on Manifolds NIPS 2018 Reverse Curriculum Generation for Reinforcement Learning CORL 2017