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Jacob Steinhardt

67 papers · 2011–2025 · 9 venues · across top CS/AI venues

This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 14 separate collaboration groups - the largest holds only 48% of them. Pick the group below that matches the researcher you mean. How a shared name is split.

Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.

Which Jacob Steinhardt?

5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.

with Percy Liang, Erik Jones, Alexander Wei 32 papers · 2014–2025 · ICML, NeurIPS, ICLR Hide ▲
Adversaries Can Misuse Combinations of Safe Models ICML 2025 Eliciting Language Model Behaviors with Investigator Agents ICML 2025 Uncovering Gaps in How Humans and LLMs Interpret Subjective Language ICLR 2025 Approaching Human-Level Forecasting with Language Models NeurIPS 2024 Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation ICML 2024 Feedback Loops With Language Models Drive In-Context Reward Hacking ICML 2024 Overthinking the Truth: Understanding how Language Models Process False Demonstrations ICLR 2024 Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations ICML 2023 Automatically Auditing Large Language Models via Discrete Optimization ICML 2023 Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition NeurIPS 2023 Jailbroken: How Does LLM Safety Training Fail? NeurIPS 2023 Mass-Producing Failures of Multimodal Systems with Language Models NeurIPS 2023 Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws AISTATS 2023 Supply-Side Equilibria in Recommender Systems NeurIPS 2023 Capturing Failures of Large Language Models via Human Cognitive Biases NeurIPS 2022 More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize ICML 2022 Predicting Out-of-Distribution Error with the Projection Norm ICML 2022 The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models ICLR 2022 Grounding Representation Similarity Through Statistical Testing NeurIPS 2021 Learning Equilibria in Matching Markets from Bandit Feedback NeurIPS 2021 Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming NeurIPS 2020 Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020 Certified Defenses against Adversarial Examples ICLR 2018 Semidefinite relaxations for certifying robustness to adversarial examples NeurIPS 2018 Certified Defenses for Data Poisoning Attacks NeurIPS 2017 Unsupervised Risk Estimation Using Only Conditional Independence Structure NeurIPS 2016 Learning Fast-Mixing Models for Structured Prediction ICML 2015 Learning Where to Sample in Structured Prediction AISTATS 2015 Learning with Relaxed Supervision NeurIPS 2015 Reified Context Models ICML 2015 Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm ICML 2014 Filtering with Abstract Particles ICML 2014
9 papers whose co-authors appear nowhere else under this name
Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision ICLR 2025 What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning? ICML 2025 Which Attention Heads Matter for In-Context Learning? ICML 2025 Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 Small ICLR 2023 Progress measures for grokking via mechanistic interpretability ICLR 2023 Identifying Statistical Bias in Dataset Replication ICML 2020 Minimax rates for memory-bounded sparse linear regression COLT 2015 Flexible Martingale Priors for Deep Hierarchies AISTATS 2012 Finite-Time Regional Verification of Stochastic Nonlinear Systems RSS 2011

Venues · all papers under this name

ICML (21) NeurIPS (18) ICLR (16) CVPR (4) AISTATS (3) COLT (2) ACL (1) ICCV (1) RSS (1)