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Richard Diehl Martinez
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2020 – today
- 2024
- [c5]Richard Diehl Martinez, Pietro Lesci, Paula Buttery:
Tending Towards Stability: Convergence Challenges in Small Language Models. EMNLP (Findings) 2024: 3275-3286 - [c4]Richard Diehl Martinez, Zebulon Goriely, Andrew Caines, Paula Buttery, Lisa Beinborn:
Mitigating Frequency Bias and Anisotropy in Language Model Pre-Training with Syntactic Smoothing. EMNLP 2024: 5999-6011 - [i11]Richard Diehl Martinez, Pietro Lesci, Paula Buttery:
Tending Towards Stability: Convergence Challenges in Small Language Models. CoRR abs/2410.11451 (2024) - [i10]Richard Diehl Martinez, Zebulon Goriely, Andrew Caines, Paula Buttery, Lisa Beinborn:
Mitigating Frequency Bias and Anisotropy in Language Model Pre-Training with Syntactic Smoothing. CoRR abs/2410.11462 (2024) - [i9]Suchir Salhan, Richard Diehl Martinez, Zebulon Goriely, Paula Buttery:
Less is More: Pre-Training Cross-Lingual Small-Scale Language Models with Cognitively-Plausible Curriculum Learning Strategies. CoRR abs/2410.22886 (2024) - [i8]Zebulon Goriely, Richard Diehl Martinez, Andrew Caines, Lisa Beinborn, Paula Buttery:
From Babble to Words: Pre-Training Language Models on Continuous Streams of Phonemes. CoRR abs/2410.22906 (2024) - 2023
- [i7]Richard Diehl Martinez, Zebulon Goriely, Hope McGovern, Christopher Davis, Andrew Caines, Paula Buttery, Lisa Beinborn:
CLIMB: Curriculum Learning for Infant-inspired Model Building. CoRR abs/2311.08886 (2023) - 2021
- [c3]Richard Diehl Martinez, Scott Novotney, Ivan Bulyko, Ariya Rastrow, Andreas Stolcke, Ankur Gandhe:
Attention-based Contextual Language Model Adaptation for Speech Recognition. ACL/IJCNLP (Findings) 2021: 1994-2003 - [i6]Richard Diehl Martinez, Scott Novotney, Ivan Bulyko, Ariya Rastrow, Andreas Stolcke, Ankur Gandhe:
Attention-based Contextual Language Model Adaptation for Speech Recognition. CoRR abs/2106.01451 (2021) - 2020
- [c2]Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang:
Automatically Neutralizing Subjective Bias in Text. AAAI 2020: 480-489
2010 – 2019
- 2019
- [c1]Geoffrey Angus, Richard Diehl Martinez, Mitchell L. Stevens, Andreas Paepcke:
Via: Illuminating Academic Pathways at Scale. L@S 2019: 23:1-23:10 - [i5]Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang:
Automatically Neutralizing Subjective Bias in Text. CoRR abs/1911.09709 (2019) - 2018
- [i4]Rooz Mahdavian, Richard Diehl Martinez:
Theory of Machine Networks: A Case Study. CoRR abs/1806.09785 (2018) - [i3]Rooz Mahdavian, Richard Diehl Martinez:
Ignition: An End-to-End Supervised Model for Training Simulated Self-Driving Vehicles. CoRR abs/1806.11349 (2018) - [i2]Richard Diehl Martinez, John Kaleialoha Kamalu:
Using General Adversarial Networks for Marketing: A Case Study of Airbnb. CoRR abs/1806.11432 (2018) - [i1]Richard Diehl Martinez, Geoffrey Angus, Rooz Mahdavian:
Grapevine: A Wine Prediction Algorithm Using Multi-dimensional Clustering Methods. CoRR abs/1807.00692 (2018)
Coauthor Index
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last updated on 2024-12-01 01:16 CET by the dblp team
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