Search Results for author: Gerard de Melo

Found 100 papers, 34 papers with code

Multi-Scale Distribution Deep Variational Autoencoder for Explanation Generation

no code implementations Findings (ACL) 2022 ZeFeng Cai, LinLin Wang, Gerard de Melo, Fei Sun, Liang He

Generating explanations for recommender systems is essential for improving their transparency, as users often wish to understand the reason for receiving a specified recommendation.

Explanation Generation Recommendation Systems

EmoTag1200: Understanding the Association between Emojis and Emotions

no code implementations EMNLP 2020 Abu Awal Md Shoeb, Gerard de Melo

Given the growing ubiquity of emojis in language, there is a need for methods and resources that shed light on their meaning and communicative role.

Personality Predictive Lexical Cues and Their Correlations

no code implementations RANLP 2021 Xiaoli He, Gerard de Melo

In recent years, a number of studies have used linear models for personality prediction based on text.

CommitBench: A Benchmark for Commit Message Generation

1 code implementation8 Mar 2024 Maximilian Schall, Tamara Czinczoll, Gerard de Melo

Writing commit messages is a tedious daily task for many software developers, and often remains neglected.

NextLevelBERT: Investigating Masked Language Modeling with Higher-Level Representations for Long Documents

1 code implementation27 Feb 2024 Tamara Czinczoll, Christoph Hönes, Maximilian Schall, Gerard de Melo

While (large) language models have significantly improved over the last years, they still struggle to sensibly process long sequences found, e. g., in books, due to the quadratic scaling of the underlying attention mechanism.

Document Classification Language Modelling +4

MedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models

no code implementations20 Dec 2023 Yan Cai, LinLin Wang, Ye Wang, Gerard de Melo, Ya zhang, Yanfeng Wang, Liang He

The emergence of various medical large language models (LLMs) in the medical domain has highlighted the need for unified evaluation standards, as manual evaluation of LLMs proves to be time-consuming and labor-intensive.

Clinical Knowledge

Efficient Parallelization Layouts for Large-Scale Distributed Model Training

1 code implementation9 Nov 2023 Johannes Hagemann, Samuel Weinbach, Konstantin Dobler, Maximilian Schall, Gerard de Melo

In this work, we conduct a comprehensive ablation study of possible training configurations for large language models.

IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization

no code implementations18 Oct 2023 Zengguang Hao, Jie Zhang, Binxia Xu, Yafang Wang, Gerard de Melo, Xiaolong Li

Intent detection and identification from multi-turn dialogue has become a widely explored technique in conversational agents, for example, voice assistants and intelligent customer services.

Intent Detection

FARSEC: A Reproducible Framework for Automatic Real-Time Vehicle Speed Estimation Using Traffic Cameras

1 code implementation25 Sep 2023 Lucas Liebe, Franz Sauerwald, Sylwester Sawicki, Matthias Schneider, Leo Schuhmann, Tolga Buz, Paul Boes, Ahmad Ahmadov, Gerard de Melo

To address this, we provide a novel framework for automatic real-time vehicle speed calculation, which copes with more diverse data from publicly available traffic cameras to achieve greater robustness.

Management Vehicle Speed Estimation

Connecting the Dots: What Graph-Based Text Representations Work Best for Text Classification Using Graph Neural Networks?

1 code implementation23 May 2023 Margarita Bugueño, Gerard de Melo

Given the success of Graph Neural Networks (GNNs) for structure-aware machine learning, many studies have explored their use for text classification, but mostly in specific domains with limited data characteristics.

graph construction Graph Mining +2

FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models

2 code implementations23 May 2023 Konstantin Dobler, Gerard de Melo

However, if we want to use a new tokenizer specialized for the target language, we cannot transfer the source model's embedding matrix.

NER Semantic Similarity +2

MultiModal Bias: Introducing a Framework for Stereotypical Bias Assessment beyond Gender and Race in Vision Language Models

1 code implementation16 Mar 2023 Sepehr Janghorbani, Gerard de Melo

Recent breakthroughs in self supervised training have led to a new class of pretrained vision language models.

Democratization of Retail Trading: Can Reddit's WallStreetBets Outperform Investment Bank Analysts?

no code implementations31 Dec 2022 Tolga Buz, Gerard de Melo

We present a data-driven empirical study of investment recommendations of WSB in comparison to recommendations made by leading investment banks, based on more than 1. 6 million WSB posts published since 2018.

Frozen CLIP Models are Efficient Video Learners

2 code implementations6 Aug 2022 Ziyi Lin, Shijie Geng, Renrui Zhang, Peng Gao, Gerard de Melo, Xiaogang Wang, Jifeng Dai, Yu Qiao, Hongsheng Li

Video recognition has been dominated by the end-to-end learning paradigm -- first initializing a video recognition model with weights of a pretrained image model and then conducting end-to-end training on videos.

Ranked #26 on Action Classification on Kinetics-400 (using extra training data)

Action Classification Video Recognition

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

3 code implementations9 Jun 2022 Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew Dai, Andrew La, Andrew Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakaş, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartłomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, César Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodola, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, Francois Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocoń, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, Jose Hernandez-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras-Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Şenel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, Maria Jose Ramírez Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Orduna Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael Ivanitskiy, Michael Starritt, Michael Strube, Michał Swędrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T, Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha S. Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Miłkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima, Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, ZiRui Wang, Ziyi Wu

BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.

Common Sense Reasoning Math +1

Art Creation with Multi-Conditional StyleGANs

1 code implementation23 Feb 2022 Konstantin Dobler, Florian Hübscher, Jan Westphal, Alejandro Sierra-Múnera, Gerard de Melo, Ralf Krestel

Our approach is based on the StyleGAN neural network architecture, but incorporates a custom multi-conditional control mechanism that provides fine-granular control over characteristics of the generated paintings, e. g., with regard to the perceived emotion evoked in a spectator.

Generative Adversarial Network

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

2 code implementations6 Dec 2021 Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahendiran, Simon Mille, Ashish Shrivastava, Samson Tan, Tongshuang Wu, Jascha Sohl-Dickstein, Jinho D. Choi, Eduard Hovy, Ondrej Dusek, Sebastian Ruder, Sajant Anand, Nagender Aneja, Rabin Banjade, Lisa Barthe, Hanna Behnke, Ian Berlot-Attwell, Connor Boyle, Caroline Brun, Marco Antonio Sobrevilla Cabezudo, Samuel Cahyawijaya, Emile Chapuis, Wanxiang Che, Mukund Choudhary, Christian Clauss, Pierre Colombo, Filip Cornell, Gautier Dagan, Mayukh Das, Tanay Dixit, Thomas Dopierre, Paul-Alexis Dray, Suchitra Dubey, Tatiana Ekeinhor, Marco Di Giovanni, Tanya Goyal, Rishabh Gupta, Louanes Hamla, Sang Han, Fabrice Harel-Canada, Antoine Honore, Ishan Jindal, Przemyslaw K. Joniak, Denis Kleyko, Venelin Kovatchev, Kalpesh Krishna, Ashutosh Kumar, Stefan Langer, Seungjae Ryan Lee, Corey James Levinson, Hualou Liang, Kaizhao Liang, Zhexiong Liu, Andrey Lukyanenko, Vukosi Marivate, Gerard de Melo, Simon Meoni, Maxime Meyer, Afnan Mir, Nafise Sadat Moosavi, Niklas Muennighoff, Timothy Sum Hon Mun, Kenton Murray, Marcin Namysl, Maria Obedkova, Priti Oli, Nivranshu Pasricha, Jan Pfister, Richard Plant, Vinay Prabhu, Vasile Pais, Libo Qin, Shahab Raji, Pawan Kumar Rajpoot, Vikas Raunak, Roy Rinberg, Nicolas Roberts, Juan Diego Rodriguez, Claude Roux, Vasconcellos P. H. S., Ananya B. Sai, Robin M. Schmidt, Thomas Scialom, Tshephisho Sefara, Saqib N. Shamsi, Xudong Shen, Haoyue Shi, Yiwen Shi, Anna Shvets, Nick Siegel, Damien Sileo, Jamie Simon, Chandan Singh, Roman Sitelew, Priyank Soni, Taylor Sorensen, William Soto, Aman Srivastava, KV Aditya Srivatsa, Tony Sun, Mukund Varma T, A Tabassum, Fiona Anting Tan, Ryan Teehan, Mo Tiwari, Marie Tolkiehn, Athena Wang, Zijian Wang, Gloria Wang, Zijie J. Wang, Fuxuan Wei, Bryan Wilie, Genta Indra Winata, Xinyi Wu, Witold Wydmański, Tianbao Xie, Usama Yaseen, Michael A. Yee, Jing Zhang, Yue Zhang

Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on.

Data Augmentation

Dense Contrastive Visual-Linguistic Pretraining

no code implementations24 Sep 2021 Lei Shi, Kai Shuang, Shijie Geng, Peng Gao, Zuohui Fu, Gerard de Melo, Yunpeng Chen, Sen Su

To overcome these issues, we propose unbiased Dense Contrastive Visual-Linguistic Pretraining (DCVLP), which replaces the region regression and classification with cross-modality region contrastive learning that requires no annotations.

Contrastive Learning Data Augmentation +2

Data Augmentation with Adversarial Training for Cross-Lingual NLI

no code implementations ACL 2021 Xin Dong, Yaxin Zhu, Zuohui Fu, Dongkuan Xu, Gerard de Melo

Due to recent pretrained multilingual representation models, it has become feasible to exploit labeled data from one language to train a cross-lingual model that can then be applied to multiple new languages.

Cross-Lingual Natural Language Inference Data Augmentation

R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling

1 code implementation ACL 2021 Xiang Hu, Haitao Mi, Zujie Wen, Yafang Wang, Yi Su, Jing Zheng, Gerard de Melo

Human language understanding operates at multiple levels of granularity (e. g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combined.

Language Modelling

Guilt by Association: Emotion Intensities in Lexical Representations

no code implementations EMNLP 2021 Shahab Raji, Gerard de Melo

What do word vector representations reveal about the emotions associated with words?

Context-Aware Interaction Network for Question Matching

no code implementations EMNLP 2021 Zhe Hu, Zuohui Fu, Yu Yin, Gerard de Melo

Impressive milestones have been achieved in text matching by adopting a cross-attention mechanism to capture pertinent semantic connections between two sentence representations.

Sentence Text Matching

Faithfully Explainable Recommendation via Neural Logic Reasoning

1 code implementation NAACL 2021 Yaxin Zhu, Yikun Xian, Zuohui Fu, Gerard de Melo, Yongfeng Zhang

Knowledge graphs (KG) have become increasingly important to endow modern recommender systems with the ability to generate traceable reasoning paths to explain the recommendation process.

Decision Making Explainable Recommendation +3

Fast and Effective Biomedical Entity Linking Using a Dual Encoder

1 code implementation EACL (Louhi) 2021 Rajarshi Bhowmik, Karl Stratos, Gerard de Melo

Additionally, we modify our dual encoder model for end-to-end biomedical entity linking that performs both mention span detection and entity disambiguation and out-performs two recently proposed models.

Entity Disambiguation Entity Linking

Assessing Emoji Use in Modern Text Processing Tools

no code implementations ACL 2021 Abu Awal Md Shoeb, Gerard de Melo

Emojis have become ubiquitous in digital communication, due to their visual appeal as well as their ability to vividly convey human emotion, among other factors.

Part-Of-Speech Tagging Sentiment Analysis

Query Distillation: BERT-based Distillation for Ensemble Ranking

no code implementations COLING 2020 Wangshu Zhang, Junhong Liu, Zujie Wen, Yafang Wang, Gerard de Melo

We present a novel two-stage distillation method for ranking problems that allows a smaller student model to be trained while benefitting from the better performance of the teacher model, providing better control of the inference latency and computational burden.

Knowledge Distillation

Domain-Specific Sentiment Lexicons Induced from Labeled Documents

no code implementations COLING 2020 Sm Mazharul Islam, Xin Dong, Gerard de Melo

Sentiment analysis is an area of substantial relevance both in industry and in academia, including for instance in social studies.

Sentiment Analysis

Sentence Analogies: Linguistic Regularities in Sentence Embeddings

no code implementations COLING 2020 Xunjie Zhu, Gerard de Melo

While important properties of word vector representations have been studied extensively, far less is known about the properties of sentence vector representations.

Sentence Sentence Embedding +1

Cross-Domain Learning for Classifying Propaganda in Online Contents

2 code implementations13 Nov 2020 Liqiang Wang, Xiaoyu Shen, Gerard de Melo, Gerhard Weikum

Prior work has focused on supervised learning with training data from the same domain.

CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation

1 code implementation29 Oct 2020 Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang

User profiles can capture prominent user behaviors from the history, and provide valuable signals about which kinds of path patterns are more likely to lead to potential items of interest for the user.

Explainable Recommendation Knowledge Graphs +1

GitEvolve: Predicting the Evolution of GitHub Repositories

1 code implementation9 Oct 2020 Honglu Zhou, Hareesh Ravi, Carlos M. Muniz, Vahid Azizi, Linda Ness, Gerard de Melo, Mubbasir Kapadia

Given its crucial role, there is a need to better understand and model the dynamics of GitHub as a social platform.

Representation Learning

COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce

no code implementations21 Aug 2020 Zuohui Fu, Yikun Xian, Yaxin Zhu, Yongfeng Zhang, Gerard de Melo

In this work, we present a new dataset for conversational recommendation over knowledge graphs in e-commerce platforms called COOKIE.

Knowledge Graphs

Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification

no code implementations29 Jul 2020 Xin Dong, Yaxin Zhu, Yupeng Zhang, Zuohui Fu, Dongkuan Xu, Sen yang, Gerard de Melo

The resulting model then serves as a teacher to induce labels for unlabeled target language samples that can be used during further adversarial training, allowing us to gradually adapt our model to the target language.

General Classification intent-classification +4

Contrastive Visual-Linguistic Pretraining

no code implementations26 Jul 2020 Lei Shi, Kai Shuang, Shijie Geng, Peng Su, Zhengkai Jiang, Peng Gao, Zuohui Fu, Gerard de Melo, Sen Su

We evaluate CVLP on several down-stream tasks, including VQA, GQA and NLVR2 to validate the superiority of contrastive learning on multi-modality representation learning.

Contrastive Learning regression +2

Incorporating Pragmatic Reasoning Communication into Emergent Language

no code implementations NeurIPS 2020 Yipeng Kang, Tonghan Wang, Gerard de Melo

Emergentism and pragmatics are two research fields that study the dynamics of linguistic communication along substantially different timescales and intelligence levels.

Multi-agent Reinforcement Learning Reinforcement Learning (RL) +2

TIME: Text and Image Mutual-Translation Adversarial Networks

no code implementations27 May 2020 Bingchen Liu, Kunpeng Song, Yizhe Zhu, Gerard de Melo, Ahmed Elgammal

Focusing on text-to-image (T2I) generation, we propose Text and Image Mutual-Translation Adversarial Networks (TIME), a lightweight but effective model that jointly learns a T2I generator G and an image captioning discriminator D under the Generative Adversarial Network framework.

Generative Adversarial Network Image Captioning +3

Character Matters: Video Story Understanding with Character-Aware Relations

no code implementations9 May 2020 Shijie Geng, Ji Zhang, Zuohui Fu, Peng Gao, Hang Zhang, Gerard de Melo

Without identifying the connection between appearing people and character names, a model is not able to obtain a genuine understanding of the plots.

Question Answering

Are Emojis Emotional? A Study to Understand the Association between Emojis and Emotions

no code implementations2 May 2020 Abu Shoeb, Gerard de Melo

Given the growing ubiquity of emojis in language, there is a need for methods and resources that shed light on their meaning and communicative role.

Explainable Link Prediction for Emerging Entities in Knowledge Graphs

1 code implementation1 May 2020 Rajarshi Bhowmik, Gerard de Melo

Despite their large-scale coverage, cross-domain knowledge graphs invariably suffer from inherent incompleteness and sparsity.

Knowledge Graphs Link Prediction +1

Inducing Universal Semantic Tag Vectors

no code implementations LREC 2020 Da Huo, Gerard de Melo

Given the well-established usefulness of part-of-speech tag annotations in many syntactically oriented downstream NLP tasks, the recently proposed notion of semantic tagging (Bjerva et al. 2016) aims at tagging words with tags informed by semantic distinctions, which are likely to be useful across a range of semantic tasks.

TAG

HID: Hierarchical Multiscale Representation Learning for Information Diffusion

2 code implementations19 Apr 2020 Honglu Zhou, Shuyuan Xu, Zuohui Fu, Gerard de Melo, Yongfeng Zhang, Mubbasir Kapadia

In this paper, we present a Hierarchical Information Diffusion (HID) framework by integrating user representation learning and multiscale modeling.

Representation Learning

Sentence Analogies: Exploring Linguistic Relationships and Regularities in Sentence Embeddings

no code implementations9 Mar 2020 Xunjie Zhu, Gerard de Melo

While important properties of word vector representations have been studied extensively, far less is known about the properties of sentence vector representations.

Sentence Sentence Embedding +1

Knowledge Graphs

2 code implementations4 Mar 2020 Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutierrez, José Emilio Labra Gayo, Sabrina Kirrane, Sebastian Neumaier, Axel Polleres, Roberto Navigli, Axel-Cyrille Ngonga Ngomo, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, Antoine Zimmermann

In this paper we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data.

Knowledge Graphs

Long Short-Term Sample Distillation

no code implementations2 Mar 2020 Liang Jiang, Zujie Wen, Zhongping Liang, Yafang Wang, Gerard de Melo, Zhe Li, Liangzhuang Ma, Jiaxing Zhang, Xiaolong Li, Yuan Qi

The long-term teacher draws on snapshots from several epochs ago in order to provide steadfast guidance and to guarantee teacher--student differences, while the short-term one yields more up-to-date cues with the goal of enabling higher-quality updates.

ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs

no code implementations29 Jan 2020 Zuohui Fu, Yikun Xian, Shijie Geng, Yingqiang Ge, Yuting Wang, Xin Dong, Guang Wang, Gerard de Melo

A number of cross-lingual transfer learning approaches based on neural networks have been proposed for the case when large amounts of parallel text are at our disposal.

Cross-Lingual Transfer Sentence +3

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation

no code implementations18 Dec 2019 Xin Dong, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, Gerard de Melo

In practice, however, these two sets of reviews are notably different: users' reviews reflect a variety of items that they have bought and are hence very heterogeneous in their topics, while an item's reviews pertain only to that single item and are thus topically homogeneous.

Recommendation Systems

A Robust Self-Learning Framework for Cross-Lingual Text Classification

no code implementations IJCNLP 2019 Xin Dong, Gerard de Melo

Based on massive amounts of data, recent pretrained contextual representation models have made significant strides in advancing a number of different English NLP tasks.

General Classification Self-Learning +4

SCALOR: Generative World Models with Scalable Object Representations

2 code implementations ICLR 2020 Jindong Jiang, Sepehr Janghorbani, Gerard de Melo, Sungjin Ahn

Scalability in terms of object density in a scene is a primary challenge in unsupervised sequential object-oriented representation learning.

Object Representation Learning

EmoTag -- Towards an Emotion-Based Analysis of Emojis

no code implementations RANLP 2019 Abu Awal Md Shoeb, Shahab Raji, Gerard de Melo

We evaluate the induced emotion profiles of emojis with regard to their ability to predict word affect intensities as well as sentiment scores.

Reinforcement Knowledge Graph Reasoning for Explainable Recommendation

1 code implementation12 Jun 2019 Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang

To this end, we propose a method called Policy-Guided Path Reasoning (PGPR), which couples recommendation and interpretability by providing actual paths in a knowledge graph.

Causal Inference Decision Making +3

OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization

1 code implementation26 May 2019 Bingchen Liu, Yizhe Zhu, Zuohui Fu, Gerard de Melo, Ahmed Elgammal

Exploring the potential of GANs for unsupervised disentanglement learning, this paper proposes a novel GAN-based disentanglement framework with One-Hot Sampling and Orthogonal Regularization (OOGAN).

Disentanglement

Be Concise and Precise: Synthesizing Open-Domain Entity Descriptions from Facts

1 code implementation16 Apr 2019 Rajarshi Bhowmik, Gerard de Melo

Despite being vast repositories of factual information, cross-domain knowledge graphs, such as Wikidata and the Google Knowledge Graph, only sparsely provide short synoptic descriptions for entities.

Entity Disambiguation Knowledge Graphs

CITE: A Corpus of Image-Text Discourse Relations

1 code implementation NAACL 2019 Malihe Alikhani, Sreyasi Nag Chowdhury, Gerard de Melo, Matthew Stone

This paper presents a novel crowd-sourced resource for multimodal discourse: our resource characterizes inferences in image-text contexts in the domain of cooking recipes in the form of coherence relations.

Common Sense Reasoning

Using Multi-Sense Vector Embeddings for Reverse Dictionaries

1 code implementation WS 2019 Michael A. Hedderich, Andrew Yates, Dietrich Klakow, Gerard de Melo

However, they typically cannot serve as a drop-in replacement for conventional single-sense embeddings, because the correct sense vector needs to be selected for each word.

A Helping Hand: Transfer Learning for Deep Sentiment Analysis

no code implementations ACL 2018 Xin Dong, Gerard de Melo

Deep convolutional neural networks excel at sentiment polarity classification, but tend to require substantial amounts of training data, which moreover differs quite significantly between domains.

General Classification Sentiment Analysis +2

Generating Fine-Grained Open Vocabulary Entity Type Descriptions

1 code implementation ACL 2018 Rajarshi Bhowmik, Gerard de Melo

While large-scale knowledge graphs provide vast amounts of structured facts about entities, a short textual description can often be useful to succinctly characterize an entity and its type.

Knowledge Graphs Vocal Bursts Type Prediction

Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification

5 code implementations CVPR 2018 Xiang Long, Chuang Gan, Gerard de Melo, Jiajun Wu, Xiao Liu, Shilei Wen

In this paper, however, we show that temporal information, especially longer-term patterns, may not be necessary to achieve competitive results on common video classification datasets.

Classification General Classification +1

Multilingual Vector Representations of Words, Sentences, and Documents

no code implementations IJCNLP 2017 Gerard de Melo

Neural vector representations are now ubiquitous in all subfields of natural language processing and text mining.

Knowledge Graphs

Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval

3 code implementations30 Jun 2017 Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo

Neural IR models, such as DRMM and PACRR, have achieved strong results by successfully capturing relevance matching signals.

Ad-Hoc Information Retrieval Retrieval

PACRR: A Position-Aware Neural IR Model for Relevance Matching

3 code implementations EMNLP 2017 Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo

In order to adopt deep learning for information retrieval, models are needed that can capture all relevant information required to assess the relevance of a document to a given user query.

Ad-Hoc Information Retrieval Information Retrieval +2

Video Captioning with Multi-Faceted Attention

no code implementations TACL 2018 Xiang Long, Chuang Gan, Gerard de Melo

Recently, video captioning has been attracting an increasing amount of interest, due to its potential for improving accessibility and information retrieval.

Information Retrieval Retrieval +2

Should Algorithms for Random SAT and Max-SAT be Different?

no code implementations3 Oct 2016 Sixue Liu, Gerard de Melo

We analyze to what extent the random SAT and Max-SAT problems differ in their properties.

Medical Concept Embeddings via Labeled Background Corpora

no code implementations LREC 2016 Eneldo Loza Menc{\'\i}a, Gerard de Melo, Jinseok Nam

In recent years, we have seen an increasing amount of interest in low-dimensional vector representations of words.

Word Similarity

The Open Linguistics Working Group: Developing the Linguistic Linked Open Data Cloud

no code implementations LREC 2016 John Philip McCrae, Christian Chiarcos, Francis Bond, Philipp Cimiano, Thierry Declerck, Gerard de Melo, Jorge Gracia, Sebastian Hellmann, Bettina Klimek, Steven Moran, Petya Osenova, Antonio Pareja-Lora, Jonathan Pool

The Open Linguistics Working Group (OWLG) brings together researchers from various fields of linguistics, natural language processing, and information technology to present and discuss principles, case studies, and best practices for representing, publishing and linking linguistic data collections.

NomLex-PT: A Lexicon of Portuguese Nominalizations

no code implementations LREC 2014 Valeria de Paiva, Livy Real, Alex Rademaker, re, Gerard de Melo

This paper presents NomLex-PT, a lexical resource describing Portuguese nominalizations.

Etymological Wordnet: Tracing The History of Words

no code implementations LREC 2014 Gerard de Melo

Research on the history of words has led to remarkable insights about language and also about the history of human civilization more generally.

Bring vs. MTRoget: Evaluating automatic thesaurus translation

no code implementations LREC 2014 Lars Borin, Jens Allwood, Gerard de Melo

Evaluation of automatic language-independent methods for language technology resource creation is difficult, and confounded by a largely unknown quantity, viz.

Translation

Empirical Comparisons of MASC Word Sense Annotations

no code implementations LREC 2012 Gerard de Melo, Collin F. Baker, Nancy Ide, Rebecca J. Passonneau, Christiane Fellbaum

We analyze how different conceptions of lexical semantics affect sense annotations and how multiple sense inventories can be compared empirically, based on annotated text.

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