Cristina Garbacea
Cristina Garbacea
PostDoctoral Scholar, University of Chicago
Verified email at - Homepage
Cited by
Cited by
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
The gem benchmark: Natural language generation, its evaluation and metrics
S Gehrmann, T Adewumi, K Aggarwal, PS Ammanamanchi, ...
arXiv preprint arXiv:2102.01672, 2021
Low bit-rate speech coding with VQ-VAE and a WaveNet decoder
C Gārbacea, A van den Oord, Y Li, FSC Lim, A Luebs, O Vinyals, ...
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
An Empirical Study on Explainable Prediction of Text Complexity: Preliminaries for Text Simplification.
C Gārbacea, M Guo, S Carton, Q Mei
CoRR, 2020
Neural language generation: Formulation, methods, and evaluation
C Garbacea, Q Mei
arXiv preprint arXiv:2007.15780, 2020
Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation
C Garbacea, S Carton, S Yan, Q Mei
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification
C Garbacea, M Guo, S Carton, Q Mei
Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021
Gemv2: Multilingual nlg benchmarking in a single line of code
S Gehrmann, A Bhattacharjee, A Mahendiran, A Wang, A Papangelis, ...
arXiv preprint arXiv:2206.11249, 2022
Supporting Exploration of Historical Perspectives across Collections
D Odijk, C Gārbacea, T Schoegje, L Hollink, V de Boer, K Ribbens, ...
TPDL 2015, 2015
Why is constrained neural language generation particularly challenging?
C Garbacea, Q Mei
arXiv preprint arXiv:2206.05395, 2022
Detecting the reputation polarity of microblog posts
C Gārbacea, M Tsagkias, M de Rijke
ECAI 2014: 21st European Conference on Artificial Intelligence 263, 339, 2014
Speech coding using content latent embedding vectors and speaker latent embedding vectors
C Garbacea, AGA van den Oord, Y Li, SC Lim, A Luebs, O Vinyals, ...
US Patent 11,257,507, 2022
Combining multiple signals for semanticizing tweets: University of Amsterdam at# Microposts2015
C Gârbacea, D Odijk, D Graus, I Sijaranamual, M de Rijke
WWW’15, 2015
The Web
R White, Q Mei, M Rabinovich, P Samarati, O Alonso, B Benatallah, ...
ACM Transactions on 16 (3), 2022
Feature Selection and Data Sampling Methods for Learning Reputation Dimensions
C Gārbacea, M Tsagkias, M de Rijke
CLEF (Working Notes) 2014, 2014
Neural Language Generation for Content Adaptation: Explainable, Efficient Low-Resource Text Simplification and Evaluation
GC Garbacea
The University of Amsterdam (ILPS. UvA) at TREC 2015 Temporal Summarization Track
C Gārbacea, E Kanoulas
Adapting Pre-trained Language Models to Low-Resource Text Simplification: The Path Matters
C Garbacea, Q Mei
Conference on Lifelong Learning Agents, 1103-1119, 2022
UMSIForeseer at SemEval-2020 Task 11: Propaganda detection by fine-tuning BERT with resampling and ensemble learning
Y Jiang, C Gārbacea, Q Mei
Proceedings of the Fourteenth Workshop on Semantic Evaluation, 1841-1846, 2020
BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling
L Gui, C Gārbacea, V Veitch
arXiv preprint arXiv:2406.00832, 2024
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