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Hunter Lang
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2020 – today
- 2024
- [c14]Zejiang Shen, Hunter Lang, Bailin Wang, Yoon Kim, David A. Sontag:
Learning to Decode Collaboratively with Multiple Language Models. ACL (1) 2024: 12974-12990 - [i17]Shannon Zejiang Shen, Hunter Lang, Bailin Wang, Yoon Kim, David A. Sontag:
Learning to Decode Collaboratively with Multiple Language Models. CoRR abs/2403.03870 (2024) - [i16]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Theoretical Analysis of Weak-to-Strong Generalization. CoRR abs/2405.16043 (2024) - 2023
- [c13]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: 5549-5581 - [c12]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: 10520-10545 - [i15]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 abs/2301.06197 (2023) - 2022
- [c11]Monica N. Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag:
Leveraging Time Irreversibility with Order-Contrastive Pre-training. AISTATS 2022: 2330-2353 - [c10]Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag:
Large language models are few-shot clinical information extractors. EMNLP 2022: 1998-2022 - [c9]Hunter Lang, Monica N. Agrawal, Yoon Kim, David A. Sontag:
Co-training Improves Prompt-based Learning for Large Language Models. ICML 2022: 11985-12003 - [c8]Hunter Lang, Aravindan Vijayaraghavan, David A. Sontag:
Training Subset Selection for Weak Supervision. NeurIPS 2022 - [i14]Hunter Lang, Monica Agrawal, Yoon Kim, David A. Sontag:
Co-training Improves Prompt-based Learning for Large Language Models. CoRR abs/2202.00828 (2022) - [i13]Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag:
Large Language Models are Zero-Shot Clinical Information Extractors. CoRR abs/2205.12689 (2022) - [i12]Hunter Lang, Aravindan Vijayaraghavan, David A. Sontag:
Training Subset Selection for Weak Supervision. CoRR abs/2206.02914 (2022) - [i11]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 abs/2210.10723 (2022) - 2021
- [c7]Hunter Lang, Hoifung Poon:
Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic. AAAI 2021: 4978-4986 - [c6]Hunter Lang, Aravind Reddy, David A. Sontag, Aravindan Vijayaraghavan:
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances. AISTATS 2021: 3043-3051 - [c5]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch). ICML 2021: 5990-5999 - [p1]Hoifung Poon, Hai Wang, Hunter Lang:
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. Neuro-Symbolic Artificial Intelligence 2021: 311-336 - [i10]Hunter Lang, Aravind Reddy, David A. Sontag, Aravindan Vijayaraghavan:
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances. CoRR abs/2103.00034 (2021) - [i9]Hoifung Poon, Hai Wang, Hunter Lang:
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning. CoRR abs/2107.12591 (2021) - [i8]Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag:
Leveraging Time Irreversibility with Order-Contrastive Pre-training. CoRR abs/2111.02599 (2021) - 2020
- [i7]Pengchuan Zhang, Hunter Lang, Qiang Liu, Lin Xiao:
Statistical Adaptive Stochastic Gradient Methods. CoRR abs/2002.10597 (2020) - [i6]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Graph cuts always find a global optimum (with a catch). CoRR abs/2011.03639 (2020) - [i5]Hunter Lang, Hoifung Poon:
Self-supervised self-supervision by combining deep learning and probabilistic logic. CoRR abs/2012.12474 (2020)
2010 – 2019
- 2019
- [c4]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Block Stability for MAP Inference. AISTATS 2019: 216-225 - [c3]Hunter Lang, Lin Xiao, Pengchuan Zhang:
Using Statistics to Automate Stochastic Optimization. NeurIPS 2019: 9536-9546 - [c2]Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao:
Understanding the Role of Momentum in Stochastic Gradient Methods. NeurIPS 2019: 9630-9640 - [i4]Hunter Lang, Pengchuan Zhang, Lin Xiao:
Using Statistics to Automate Stochastic Optimization. CoRR abs/1909.09785 (2019) - [i3]Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao:
Understanding the Role of Momentum in Stochastic Gradient Methods. CoRR abs/1910.13962 (2019) - 2018
- [c1]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Optimality of Approximate Inference Algorithms on Stable Instances. AISTATS 2018: 1157-1166 - [i2]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Block Stability for MAP Inference. CoRR abs/1810.05305 (2018) - 2017
- [i1]Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan:
Alpha-expansion is Exact on Stable Instances. CoRR abs/1711.02195 (2017)
Coauthor Index
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last updated on 2024-10-07 22:08 CEST by the dblp team
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