Can Alternations Be Learned? A Machine Learning Approach To Romanian Verb Conjugation. - Liviu Petrisor Dinu; Emil Ionescu; Vlad Niculae; Octavia-Maria Sulea (RANLP, 2011)

Dealing with the Grey Sheep of the Romanian Gender System, the Neuter. - Liviu P. Dinu; Vlad Niculae; Octavia-Maria Sulea (COLING (Demos), 2012)

Learning How to Conjugate the Romanian Verb. Rules for Regular and Partially Irregular Verbs. - Liviu Petrisor Dinu; Vlad Niculae; Octavia-Maria Sulea (EACL, 2012)

The Romanian Neuter Examined Through A Two-Gender N-Gram Classification System. - Liviu P. Dinu; Vlad Niculae; Octavia-Maria Sulea (LREC, 2012)

String Distances for Near-duplicate Detection. - Iulia Danaila; Liviu P. Dinu; Vlad Niculae; Octavia-Maria Sulea (Polibits, 2012)

Comparison pattern matching and creative simile recognition. - Vlad Niculae (JSSP, 2013)

Determining is-a relationships for Textual Entailment. - Vlad Niculae; Octavian Popescu (JSSP, 2013)

Computational considerations of comparisons and similes. - Vlad Niculae; Victoria Yaneva (ACL (Student Research Workshop), 2013)

Temporal classification for historical Romanian texts. - Alina Maria Ciobanu; Anca Dinu; Liviu P. Dinu; Vlad Niculae; Octavia-Maria Sulea (LaTeCH@ACL, 2013)

Temporal Text Classification for Romanian Novels set in the Past. - Alina Maria Ciobanu; Liviu P. Dinu; Octavia-Maria Sulea; Anca Dinu; Vlad Niculae (RANLP, 2013)

Sequence Tagging for Verb Conjugation in Romanian. - Liviu P. Dinu; Octavia-Maria Sulea; Vlad Niculae (RANLP, 2013)

Romanian Syllabication Using Machine Learning. - Liviu P. Dinu; Vlad Niculae; Octavia-Maria Sulea (TSD, 2013)

API design for machine learning software: experiences from the scikit-learn project. - Lars Buitinck; Gilles Louppe; Mathieu Blondel; Fabian Pedregosa; Andreas Mueller; Olivier Grisel; Vlad Niculae; Peter Prettenhofer; Alexandre Gramfort; Jaques Grobler; Robert Layton; Jake VanderPlas; et al. (CoRR, 2013)

Temporal Text Ranking and Automatic Dating of Texts. - Vlad Niculae; Marcos Zampieri; Liviu P. Dinu; Alina Maria Ciobanu (EACL, 2014)

Brighter than Gold: Figurative Language in User Generated Comparisons. - Vlad Niculae; Cristian Danescu-Niculescu-Mizil (EMNLP, 2014)

Using a machine learning model to assess the complexity of stress systems. - Liviu P. Dinu; Alina Maria Ciobanu; Ioana Chitoran; Vlad Niculae (LREC, 2014)

Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game. - Vlad Niculae; Srijan Kumar; Jordan L. Boyd-Graber; Cristian Danescu-Niculescu-Mizil (ACL (1), 2015)

AMBRA: A Ranking Approach to Temporal Text Classification. - Marcos Zampieri; Alina Maria Ciobanu; Vlad Niculae; Liviu P. Dinu (SemEval@NAACL-HLT, 2015)

QUOTUS: The Structure of Political Media Coverage as Revealed by Quoting Patterns. - Vlad Niculae; Caroline Suen; Justine Zhang; Cristian Danescu-Niculescu-Mizil; Jure Leskovec (WWW, 2015)

Conversational Markers of Constructive Discussions. - Vlad Niculae; Cristian Danescu-Niculescu-Mizil (HLT-NAACL, 2016)

Cornell Belief and Sentiment System at TAC 2016. - Vlad Niculae; Kai Sun 006; Xilun Chen 002; Yao Cheng; Xinya Du; Esin Durmus; Arzoo Katiyar; Claire Cardie (TAC, 2016)

Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions. - Chenhao Tan; Vlad Niculae; Cristian Danescu-Niculescu-Mizil; Lillian Lee (WWW, 2016)

Argument Mining with Structured SVMs and RNNs. - Vlad Niculae; Joonsuk Park; Claire Cardie (ACL (1), 2017)

Multi-output Polynomial Networks and Factorization Machines. - Mathieu Blondel; Vlad Niculae; Takuma Otsuka; Naonori Ueda (NIPS, 2017)

A Regularized Framework for Sparse and Structured Neural Attention. - Vlad Niculae; Mathieu Blondel (NIPS, 2017)

Towards Dynamic Computation Graphs via Sparse Latent Structure. - Vlad Niculae; André F. T. Martins; Claire Cardie (EMNLP, 2018)

Interpretable Structure Induction via Sparse Attention. - Ben Peters; Vlad Niculae; André F. T. Martins (BlackboxNLP@EMNLP, 2018)

SparseMAP: Differentiable Sparse Structured Inference. - Vlad Niculae; André F. T. Martins; Mathieu Blondel; Claire Cardie (ICML, 2018)

Learning Deep Models with Linguistically-Inspired Structure. - Vlad Niculae (2018)

Latent Structure Models for Natural Language Processing. - André F. T. Martins; Tsvetomila Mihaylova; Nikita Nangia; Vlad Niculae (ACL (4), 2019)

Sparse Sequence-to-Sequence Models. - Ben Peters; Vlad Niculae; André F. T. Martins (ACL (1), 2019)

Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms. - Mathieu Blondel; André F. T. Martins; Vlad Niculae (AISTATS, 2019)

Adaptively Sparse Transformers. - Gonçalo M. Correia; Vlad Niculae; André F. T. Martins (EMNLP/IJCNLP (1), 2019)

Notes on Latent Structure Models and SPIGOT. - André F. T. Martins; Vlad Niculae (CoRR, 2019)

Understanding the Mechanics of SPIGOT: Surrogate Gradients for Latent Structure Learning. - Tsvetomila Mihaylova; Vlad Niculae; André F. T. Martins (EMNLP (1), 2020)

LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction. - Vlad Niculae; André F. T. Martins (ICML, 2020)

Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity. - Gonçalo M. Correia; Vlad Niculae; Wilker Aziz; André F. T. Martins (NeurIPS, 2020)

Sparse and Continuous Attention Mechanisms. - André F. T. Martins; António Farinhas; Marcos V. Treviso; Vlad Niculae; Pedro M. Q. Aguiar; Mário A. T. Figueiredo (NeurIPS, 2020)

Learning Binary Trees via Sparse Relaxation. - Valentina Zantedeschi; Matt J. Kusner; Vlad Niculae (CoRR, 2020)

Learning with Fenchel-Young losses. - Mathieu Blondel; André F. T. Martins; Vlad Niculae (J. Mach. Learn. Res., 2020)

Sparse And Structured Visual Attention. - Pedro Henrique Martins; Vlad Niculae; Zita Marinho; André F. T. Martins (ICIP, 2021)

Learning Binary Decision Trees by Argmin Differentiation. - Valentina Zantedeschi; Matt J. Kusner; Vlad Niculae (ICML, 2021)

How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation? - Ali Araabi; Christof Monz; Vlad Niculae (AMTA, 2022)

Sparse Communication via Mixed Distributions. - António Farinhas; Wilker Aziz; Vlad Niculae; André F. T. Martins (ICLR, 2022)

Modeling Structure with Undirected Neural Networks. - Tsvetomila Mihaylova; Vlad Niculae; André F. T. Martins (ICML, 2022)

On Target Representation in Continuous-output Neural Machine Translation. - Evgeniia Tokarchuk; Vlad Niculae (RepL4NLP@ACL, 2022)

Sparse Continuous Distributions and Fenchel-Young Losses. - André F. T. Martins; Marcos V. Treviso; António Farinhas; Pedro M. Q. Aguiar; Mário A. T. Figueiredo; Mathieu Blondel; Vlad Niculae (J. Mach. Learn. Res., 2022)

Viewing Knowledge Transfer in Multilingual Machine Translation Through a Representational Lens. - David Stap; Vlad Niculae; Christof Monz (EMNLP (Findings), 2023)

DAG Learning on the Permutahedron. - Valentina Zantedeschi; Luca Franceschi 001; Jean Kaddour; Matt J. Kusner; Vlad Niculae (ICLR, 2023)

Two derivations of Principal Component Analysis on datasets of distributions. - Vlad Niculae (CoRR, 2023)

Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair Variables. - Ali Araabi; Vlad Niculae; Christof Monz (CoRR, 2023)

Wrapped β-Gaussians with compact support for exact probabilistic modeling on manifolds. - Sergey Troshin 001; Vlad Niculae (Trans. Mach. Learn. Res., 2023)

Entropy- and Distance-Regularized Attention Improves Low-Resource Neural Machine Translation. - Ali Araabi; Vlad Niculae; Christof Monz (AMTA (1), 2024)

On Measuring Context Utilization in Document-Level MT Systems. - Wafaa Mohammed; Vlad Niculae (EACL (Findings), 2024)

Sparse and Structured Hopfield Networks. - Saul José Rodrigues dos Santos; Vlad Niculae; Daniel C. McNamee; André F. T. Martins (ICML, 2024)

The Unreasonable Effectiveness of Random Target Embeddings for Continuous-Output Neural Machine Translation. - Evgeniia Tokarchuk; Vlad Niculae (NAACL (Short Papers), 2024)

ARM: Efficient Guided Decoding with Autoregressive Reward Models. - Sergey Troshin 001; Vlad Niculae; Antske Fokkens (CoRR, 2024)

Analyzing Context Utilization of LLMs in Document-Level Translation. - Wafaa Mohammed; Vlad Niculae (CoRR, 2024)

We Augmented Whisper With kNN and You Won't Believe What Came Next. - Maya K. Nachesa; Vlad Niculae (CoRR, 2024)

Hopfield-Fenchel-Young Networks: A Unified Framework for Associative Memory Retrieval. - Saul José Rodrigues dos Santos; Vlad Niculae; Daniel C. McNamee; André F. T. Martins (CoRR, 2024)

kNN For Whisper And Its Effect On Bias And Speaker Adaptation. - Maya K. Nachesa; Vlad Niculae (NAACL (Findings), 2025)

Discrete Latent Structure in Neural Networks. - Vlad Niculae; Caio Corro; Nikita Nangia; Tsvetomila Mihaylova; André F. T. Martins (Found. Trends Signal Process., 2025)

Keep your distance: learning dispersed embeddings on $ mathbb{S}_{m}$. - Evgeniia Tokarchuk; Hua Chang Bakker; Vlad Niculae (Trans. Mach. Learn. Res., 2025)

On the Low-Rank Parametrization of Reward Models for Controlled Language Generation. - Sergey Troshin 001; Vlad Niculae; Antske Fokkens (Trans. Mach. Learn. Res., 2025)

Keep your distance: learning dispersed embeddings on 𝕊d. - Evgeniia Tokarchuk; Hua Chang Bakker; Vlad Niculae (CoRR, 2025)

Movie Facts and Fibs (MF2): A Benchmark for Long Movie Understanding. - Emmanouil Zaranis; António Farinhas; Saul José Rodrigues dos Santos; Beatriz Canaverde; Miguel Moura Ramos; Aditya K. Surikuchi; André Viveiros; Baohao Liao; Elena Belén Bueno-Benito; Nithin Sivakumaran; Pavlo Vasylenko; Shoubin Yu; et al. (CoRR, 2025)