Author

Daniele Bonadiman

Observed name: Bonadiman, Daniele

Institutions: University of Pennsylvania, The University of Texas at Austin

Observed institutions: University of Southern California, Amazon (United States), University of Trento, Hamad bin Khalifa University, Imperial College London, University of Pennsylvania, The University of Texas at Austin

ORCID: 0000-0001-5495-801X

Observed ORCID: 0000-0001-5495-801X

OpenAlex ID: A5082823549

Convolutional Neural Networks vs. Convolution Kernels: Feature Engineering for Answer Sentence Reranking

2016 · Kateryna Tymoshenko, Daniele Bonadiman, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 56

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Deep Neural Networks for Named Entity Recognition in Italian

2015 · Daniele Bonadiman, Aliaksei Severyn, et al. · Accademia University Press eBooks · 21

Effective shared representations with Multitask Learning for Community Question Answering

2017 · Daniele Bonadiman, Antonio Uva, et al. · Conference of the European Chapter of the Association for Computational Linguistics · 18

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Learning to Rank Non-Factoid Answers

2016 · Kateryna Tymoshenko, Daniele Bonadiman, et al. · ACM International Conference on Information and Knowledge Management (CIKM) · 13

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Injecting Domain Knowledge in Language Models for Task-oriented Dialogue Systems

2022 · Denis Emelin, Daniele Bonadiman, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 12

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Large Scale Question Paraphrase Retrieval with Smoothed Deep Metric Learning

2019 · Daniele Bonadiman, Anjishnu Kumar, et al. · Workshop on Noisy User-generated Text (W-NUT) · 12

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Multitask Learning with Deep Neural Networks for Community Question Answering

2017 · Daniele Bonadiman, Antonio Uva, et al. · Italian Journal of Computational Linguistics · 12

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Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model

2017 · Kateryna Tymoshenko, Daniele Bonadiman, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 11

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Injecting Relational Structural Representation in Neural Networks for Question Similarity

2018 · Antonio Uva, Daniele Bonadiman, et al. · Institutional Research Information System (Università degli Studi di Trento) · 10

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A Study on Efficiency, Accuracy and Document Structure for Answer Sentence Selection

2020 · Daniele Bonadiman, Alessandro Moschitti · International Conference on Computational Linguistics · 9

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DeAL: Decoding-time Alignment for Large Language Models

2025 · James Y. Huang, Sailik Sengupta, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 4

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Knowledge-Driven Slot Constraints for Goal-Oriented Dialogue Systems

2021 · Piyawat Lertvittayakumjorn, Daniele Bonadiman, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 3

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Injecting Relational Structural Representation in Neural Networks for Question Similarity

2018 · Antonio Uva, Daniele Bonadiman, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 3

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FLAP: Flow-Adhering Planning with Constrained Decoding in LLMs

2024 · Shamik Roy, Sailik Sengupta, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 2

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Neural Sentiment Analysis for a Real-World Application

2017 · Daniele Bonadiman, Giuseppe Castellucci, et al. · Accademia University Press eBooks · 2

Recurrent Context Window Networks for Italian Named Entity Recognizer

2016 · Daniele Bonadiman, Alessandro Moschitti, et al. · Italian Journal of Computational Linguistics · 2

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Peer Pressure: Execution-Verified Co-Evolution of Attacker and Defender Populations for Code Security

2026 · Pahwa, Khushbu, Ge, Yubin, et al. · arXiv (Cornell University)

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Plan-and-Patch: Diffusion Language Models for Agentic Planning

2026 · Kumar, Syamantak, Guo, Jiang, et al. · arXiv (Cornell University)

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