Audio-based multimedia event detection using deep recurrent neural networks. - Yun Wang 005; Leonardo Neves; Florian Metze (ICASSP, 2016)

Integrating Domain-Data Steering with Code-Profiling Tools to Debug Data-Intensive Workflows. - Vítor Silva 003; Leonardo Neves; Renan Souza 001; Alvaro L. G. A. Coutinho; Daniel de Oliveira 001; Marta Mattoso (WORKS@SC, 2016)

Visual features for context-aware speech recognition. - Abhinav Gupta 002; Yajie Miao; Leonardo Neves; Florian Metze (ICASSP, 2017)

Optimal probabilistic dense coding schemes. - Roger A. Kögler; Leonardo Neves (Quantum Inf. Process., 2017)

Multimodal Named Entity Disambiguation for Noisy Social Media Posts. - Seungwhan Moon; Leonardo Neves; Vitor Carvalho (ACL (1), 2018)

Visual Attention Model for Name Tagging in Multimodal Social Media. - Di Lu 003; Leonardo Neves; Vitor Carvalho; Ning Zhang; Heng Ji 001 (ACL (1), 2018)

Multimodal Named Entity Recognition for Short Social Media Posts. - Seungwhan Moon; Leonardo Neves; Vitor Carvalho (NAACL-HLT, 2018)

Photonic Discrete-time Quantum Walks and Applications. - Leonardo Neves; Graciana Puentes (Entropy, 2018)

Train One Get One Free: Partially Supervised Neural Network for Bug Report Duplicate Detection and Clustering. - Lahari Poddar; Leonardo Neves; William Brendel; Luís Marujo; Sergey Tulyakov; Pradeep Karuturi (NAACL-HLT (2), 2019)

Neural Rule Grounding for Low-Resource Relation Extraction. - Wenxuan Zhou; Hongtao Lin; Ziqi Wang 003; Leonardo Neves; Xiang Ren 001 (CoRR, 2019)

Learning to Annotate: Modularizing Data Augmentation for Text Classifiers with Natural Language Explanations. - Ziqi Wang 003; Yujia Qin; Wenxuan Zhou; Jun Yan 001; Qinyuan Ye; Leonardo Neves; Zhiyuan Liu 001; Xiang Ren 001 (CoRR, 2019)

Quantum Discord, Thermal Discord, and Entropy Generation in the Minimum Error Discrimination Strategy. - Omar Jiménez; Miguel Angel Solís-Prosser; Leonardo Neves; Aldo Delgado (Entropy, 2019)

LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation. - Dong-Ho Lee; Rahul Khanna; Bill Yuchen Lin; Seyeon Lee; Qinyuan Ye; Elizabeth Boschee; Leonardo Neves; Xiang Ren 001 (ACL (demo), 2020)

Social Factors in Closed-Network Content Consumption. - Parisa Kaghazgaran; Maarten W. Bos; Leonardo Neves; Neil Shah (CIKM, 2020)

The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks. - Brihi Joshi; Neil Shah; Francesco Barbieri; Leonardo Neves (COLING, 2020)

TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification. - Francesco Barbieri; José Camacho-Collados; Luis Espinosa Anke; Leonardo Neves (EMNLP (Findings), 2020)

Learning from Explanations with Neural Execution Tree. - Ziqi Wang 003; Yujia Qin; Wenxuan Zhou; Jun Yan 012; Qinyuan Ye; Leonardo Neves; Zhiyuan Liu 001; Xiang Ren 001 (ICLR, 2020)

NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction. - Wenxuan Zhou; Hongtao Lin; Bill Yuchen Lin; Ziqi Wang 003; Junyi Du; Leonardo Neves; Xiang Ren 001 (WWW, 2020)

LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation. - Dong-Ho Lee; Rahul Khanna; Bill Yuchen Lin; Jamin Chen; Seyeon Lee; Qinyuan Ye; Elizabeth Boschee; Leonardo Neves; Xiang Ren 001 (CoRR, 2020)

A Caption Is Worth A Thousand Images: Investigating Image Captions for Multimodal Named Entity Recognition. - Shuguang Chen; Gustavo Aguilar; Leonardo Neves; Thamar Solorio (CoRR, 2020)

Efficiently Mitigating Classification Bias via Transfer Learning. - Xisen Jin; Francesco Barbieri; Aida Mostafazadeh Davani; Brendan Kennedy 001; Leonardo Neves; Xiang Ren 001 (CoRR, 2020)

Adding domain data to code profiling tools to debug workflow parallel execution. - Vítor Silva 003; Leonardo Neves; Renan Souza 001; Alvaro L. G. A. Coutinho; Daniel de Oliveira 001; Marta Mattoso (Future Gener. Comput. Syst., 2020)

Data Augmentation for Graph Neural Networks. - Tong Zhao 003; Yozen Liu; Leonardo Neves; Oliver J. Woodford; Meng Jiang 001; Neil Shah (AAAI, 2021)

Mitigating Temporal-Drift: A Simple Approach to Keep NER Models Crisp. - Shuguang Chen; Leonardo Neves; Thamar Solorio (SocialNLP@NAACL, 2021)

Can images help recognize entities? A study of the role of images for Multimodal NER. - Shuguang Chen; Gustavo Aguilar; Leonardo Neves; Thamar Solorio (W-NUT, 2021)

AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media. - Koustuv Saha; Yozen Liu; Nicholas Vincent; Farhan Asif Chowdhury; Leonardo Neves; Neil Shah; Maarten W. Bos (CHI, 2021)

NED: Niche Detection in User Content Consumption Data. - Ekta Gujral; Leonardo Neves; Evangelos E. Papalexakis; Neil Shah (CIKM, 2021)

Data Augmentation for Cross-Domain Named Entity Recognition. - Shuguang Chen; Gustavo Aguilar; Leonardo Neves; Thamar Solorio (EMNLP (1), 2021)

CEAM: The Effectiveness of Cyclic and Ephemeral Attention Models of User Behavior on Social Platforms. - Farhan Asif Chowdhury; Yozen Liu; Koustuv Saha; Nicholas Vincent; Leonardo Neves; Neil Shah; Maarten W. Bos (ICWSM, 2021)

On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning. - Xisen Jin; Francesco Barbieri; Brendan Kennedy 001; Aida Mostafazadeh Davani; Leonardo Neves; Xiang Ren 001 (NAACL-HLT, 2021)

Mutual Information and Quantum Discord in Quantum State Discrimination with a Fixed Rate of Inconclusive Outcomes. - Omar Jiménez; Miguel Angel Solís-Prosser; Leonardo Neves; Aldo Delgado (Entropy, 2021)

TimeLMs: Diachronic Language Models from Twitter. - Daniel Loureiro; Francesco Barbieri; Leonardo Neves; Luis Espinosa Anke; José Camacho-Collados (ACL (demo), 2022)

Twitter Topic Classification. - Dimosthenis Antypas; Asahi Ushio; José Camacho-Collados; Vítor Silva 003; Leonardo Neves; Francesco Barbieri (COLING, 2022)

TempoWiC: An Evaluation Benchmark for Detecting Meaning Shift in Social Media. - Daniel Loureiro; Aminette D'Souza; Areej Nasser Muhajab; Isabella A. White; Gabriel Wong; Luis Espinosa Anke; Leonardo Neves; Francesco Barbieri; José Camacho-Collados (COLING, 2022)

Style Transfer as Data Augmentation: A Case Study on Named Entity Recognition. - Shuguang Chen; Leonardo Neves; Thamar Solorio (EMNLP, 2022)

Sunshine with a Chance of Smiles: How Does Weather Impact Sentiment on Social Media? - Julie Jiang; Nils Murrugarra-Llerena; Maarten W. Bos; Yozen Liu; Neil Shah; Leonardo Neves; Francesco Barbieri (ICWSM, 2022)

Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shifts. - Asahi Ushio; Francesco Barbieri; Vítor Silva 003; Leonardo Neves; José Camacho-Collados (AACL/IJCNLP (1), 2022)

TweetNLP: Cutting-Edge Natural Language Processing for Social Media. - José Camacho-Collados; Kiamehr Rezaee; Talayeh Riahi; Asahi Ushio; Daniel Loureiro; Dimosthenis Antypas; Joanne Boisson; Luis Espinosa Anke; Fangyu Liu; Eugenio Martínez-Cámara; Gonzalo Medina; Thomas Bührmann; et al. (CoRR, 2022)

SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis. - Jiaxin Pei; Vítor Silva 003; Maarten W. Bos; Yozon Liu; Leonardo Neves; David Jurgens; Francesco Barbieri (CoRR, 2022)

SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research. - Dimosthenis Antypas; Asahi Ushio; Francesco Barbieri; Leonardo Neves; Kiamehr Rezaee; Luis Espinosa Anke; Jiaxin Pei; José Camacho-Collados (EMNLP (Findings), 2023)

Predicting Future Location Categories of Users in a Large Social Platform. - Raiyan Abdul Baten; Yozen Liu; Heinrich Peters; Francesco Barbieri; Neil Shah; Leonardo Neves; Maarten W. Bos (ICWSM, 2023)

SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. - Jiaxin Pei; Vítor Silva 003; Maarten W. Bos; Yozen Liu; Leonardo Neves; David Jurgens; Francesco Barbieri (SemEval@ACL, 2023)

Tweet Insights: A Visualization Platform to Extract Temporal Insights from Twitter. - Daniel Loureiro; Kiamehr Rezaee; Talayeh Riahi; Francesco Barbieri; Leonardo Neves; Luis Espinosa Anke; José Camacho-Collados (CoRR, 2023)

Context-aware Adversarial Attack on Named Entity Recognition. - Shuguang Chen; Leonardo Neves; Thamar Solorio (CoRR, 2023)

Designing and Evaluating General-Purpose User Representations Based on Behavioral Logs from a Measurement Process Perspective: A Case Study with Snapchat. - Qixiang Fang; Zhihan Zhou 001; Francesco Barbieri; Yozen Liu; Leonardo Neves; Dong Nguyen 002; Daniel L. Oberski; Maarten W. Bos; Ron Dotsch (CoRR, 2023)

Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster. - Agostina Calabrese; Leonardo Neves; Neil Shah; Maarten W. Bos; Björn Ross; Mirella Lapata; Francesco Barbieri (ACL (Short Papers), 2024)

General-Purpose User Modeling with Behavioral Logs: A Snapchat Case Study. - Qixiang Fang; Zhihan Zhou 001; Francesco Barbieri; Yozen Liu; Leonardo Neves; Dong Nguyen 002; Daniel L. Oberski; Maarten W. Bos; Ron Dotsch (SIGIR, 2024)

USE: Dynamic User Modeling with Stateful Sequence Models. - Zhihan Zhou 001; Qixiang Fang; Leonardo Neves; Francesco Barbieri; Yozen Liu; Han Liu 001; Maarten W. Bos; Ron Dotsch (CoRR, 2024)

Enhancing Item Tokenization for Generative Recommendation through Self-Improvement. - Runjin Chen; Mingxuan Ju; Ngoc Bui; Dimosthenis Antypas; Stanley Cai; Xiaopeng Wu; Leonardo Neves; Zhangyang Wang; Neil Shah; Tong Zhao 003 (CoRR, 2024)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Clark Mingxuan Ju; Neil Shah; Tong Zhao 003 (CoRR, 2024)

Unpacking the exploration-exploitation tradeoff on Snapchat: The relationships between users' exploration-exploitation interests and server log data. - Diego Gómez-Zará; Yozen Liu; Leonardo Neves; Neil Shah; Maarten W. Bos (Comput. Hum. Behav., 2024)

Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat. - Clark Mingxuan Ju; Leonardo Neves; Bhuvesh Kumar; Liam Collins; Tong Zhao 003; Yuwei Qiu; Qing Dou; Yang Zhou; Sohail Nizam; Rengim Aykan Ozturk; Yvette Liu; Sen Yang; et al. (SIGIR, 2025)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Mingxuan Ju; Neil Shah; Tong Zhao 003 (WWW, 2025)

Revisiting Self-attention for Cross-domain Sequential Recommendation. - Clark Mingxuan Ju; Leonardo Neves; Bhuvesh Kumar; Liam Collins; Tong Zhao 003; Yuwei Qiu; Qing Dou; Sohail Nizam; Sen Yang; Neil Shah (CoRR, 2025)

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. - Ngoc Bui; Menglin Yang 001; Runjin Chen; Leonardo Neves; Mingxuan Ju; Rex Ying; Neil Shah; Tong Zhao 003 (CoRR, 2025)

Generative Recommendation with Semantic IDs: A Practitioner's Handbook. - Clark Mingxuan Ju; Liam Collins; Leonardo Neves; Bhuvesh Kumar; Louis Yufeng Wang; Tong Zhao 003; Neil Shah (CoRR, 2025)