Hunter Lang

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 31

Top Topics

Top Venues

Publications

Zejiang Shen, Hunter Lang, Bailin Wang, Yoon Kim, David A. Sontag
Learning to Decode Collaboratively with Multiple Language Models. ACL (1) (2024)
Shannon Zejiang Shen, Hunter Lang, Bailin Wang, Yoon Kim, David A. Sontag
Learning to Decode Collaboratively with Multiple Language Models. CoRR (2024)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Theoretical Analysis of Weak-to-Strong Generalization. CoRR (2024)
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
Who Should Predict? Exact Algorithms For Learning to Defer to Humans. CoRR (2023)
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
Who Should Predict? Exact Algorithms For Learning to Defer to Humans. AISTATS (2023)
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag
TabLLM: Few-shot Classification of Tabular Data with Large Language Models. AISTATS (2023)
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag
TabLLM: Few-shot Classification of Tabular Data with Large Language Models. CoRR (2022)
Hunter Lang, Aravindan Vijayaraghavan, David A. Sontag
Training Subset Selection for Weak Supervision. NeurIPS (2022)
Monica N. Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag
Leveraging Time Irreversibility with Order-Contrastive Pre-training. AISTATS (2022)
Hunter Lang, Monica N. Agrawal, Yoon Kim, David A. Sontag
Co-training Improves Prompt-based Learning for Large Language Models. ICML (2022)
Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag
Large Language Models are Zero-Shot Clinical Information Extractors. CoRR (2022)
Hunter Lang, Monica Agrawal, Yoon Kim, David A. Sontag
Co-training Improves Prompt-based Learning for Large Language Models. CoRR (2022)
Hunter Lang, Aravindan Vijayaraghavan, David A. Sontag
Training Subset Selection for Weak Supervision. CoRR (2022)
Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag
Large language models are few-shot clinical information extractors. EMNLP (2022)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch). ICML (2021)
Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag
Leveraging Time Irreversibility with Order-Contrastive Pre-training. CoRR (2021)
Hunter Lang, Hoifung Poon
Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic. AAAI (2021)
Hunter Lang, Aravind Reddy, David A. Sontag, Aravindan Vijayaraghavan
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances. AISTATS (2021)
Hoifung Poon, Hai Wang, Hunter Lang
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. CoRR (2021)
Hunter Lang, Aravind Reddy, David A. Sontag, Aravindan Vijayaraghavan
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances. CoRR (2021)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Graph cuts always find a global optimum (with a catch). CoRR (2020)
Hunter Lang, Hoifung Poon
Self-supervised self-supervision by combining deep learning and probabilistic logic. CoRR (2020)
Pengchuan Zhang, Hunter Lang, Qiang Liu, Lin Xiao
Statistical Adaptive Stochastic Gradient Methods. CoRR (2020)
Hunter Lang, Pengchuan Zhang, Lin Xiao
Using Statistics to Automate Stochastic Optimization. CoRR (2019)
Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao
Understanding the Role of Momentum in Stochastic Gradient Methods. CoRR (2019)
Hunter Lang, Lin Xiao, Pengchuan Zhang
Using Statistics to Automate Stochastic Optimization. NeurIPS (2019)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Block Stability for MAP Inference. AISTATS (2019)
Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao
Understanding the Role of Momentum in Stochastic Gradient Methods. NeurIPS (2019)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Optimality of Approximate Inference Algorithms on Stable Instances. AISTATS (2018)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Block Stability for MAP Inference. CoRR (2018)
Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan
Alpha-expansion is Exact on Stable Instances. CoRR (2017)