Hi!

I recently got my Ph.D. in Computer Science from Columbia University where I was part of the natural language processing group . My Ph.D. research advisor was Smaranda Muresan. My dissertation was on Computational Models of Argument Structure and Argument Quality for Understanding Misinformation [ link ].

Prior to Columbia, I worked as a Research Associate at the Center for Complex Engineering Systems (CCES) that is held jointly at the King Abdulaziz City for Science and Technology (KACST) and the Massachusetts Institute of Technology (MIT).

Email:   tariq [at] cs [dot] columbia [dot] edu
Resume: Full Resume, Short 1-page Resume

Research Interests

My research is in natural language understanding and machine learning. I am interested in studying how can models of Argument Structure and Argument Quality (Fallacy) improve our understanding of Misinformation and our ability to automate the fact-checking pipeline. I work on problems across the full fact-checking pipeline that include: check-worthiness detection, evidence retrieval, and claim verification. I mainly work on complimenting pre-trained language models with external knowledge relevant to these tasks (e.g. discourse information for argumentation mining, argumentation for check-worthiness detection, and instruction-based prompts for detecting fallacies). I also work on analyzing the robustness of these models under adversarial attacks.

Selected Publications

• Multitask Instruction-based Prompting for Fallacy Recognition
  Tariq Alhindi, Tuhin Chakrabarty, Elena Musi and Smaranda Muresan.
  To appear in Proceedings of the Conference on Empirical Methods in Natural Language Processing ( EMNLP ) 2022.
  

• What to Fact-Check: Guiding Check-Worthy Information Detection in News Articles through Argumentative Discourse Structure
  Tariq Alhindi, Brennan McManus and Smaranda Muresan.
  Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue ( SIGDIAL ) 2021.
  [ code + data ] [ slides ] [ video-short ] [ video-long ] [ BibTeX ]

• Fact vs. Opinion: the Role of Argumentation Features in News Classification
  Tariq Alhindi, Smaranda Muresan, and Daniel Preotiuc-Pietro
  Proceedings of the 28th International Conference on Computational Linguistics ( COLING ) 2020.
  [ code ] [ data1 ] [ data2 ] [ slides ]
  [ video ] [ twitter ] [ BibTeX ]

• DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking
  Christopher Hidey, Tuhin Chakrabarty, Tariq Alhindi, Siddharth Varia, Kriste Krstovski, Mona Diab,
  and Smaranda Muresan
  Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics ( ACL ) 2020.
  [ code ] [ data ] [ slides ]
  [ video ] [ BibTeX ]

• ''Sharks are not the threat humans are'': Argument Component Segmentation in School Student Essays
  Tariq Alhindi and Debanjan Ghosh
  Proceedings of the 16th Workshop on Innovative Use of NLP for Building Educational Applications
  ( BEA ), EACL 2021.
  [ code + data ] [ slides ] [ BibTeX ]

• AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking
  Tariq Alhindi, Amal Alabdulkarim, Ali Alshehri, Muhammad Abdul-Mageed and Preslav Nakov
  Proceedings of the 4th workshop on NLP for Internet Freedom
  ( NLP4IF ): Censorship, Disinformation and Propaganda. NAACL 2021.
  [ data ] [ poster ] [ BibTeX ]

• Fine-Tuned Neural Models for Propaganda Detection at the Sentence and Fragment levels
  Tariq Alhindi, Jonas Pfeiffer, and Smaranda Muresan
  [ CUNLP @leaderboard ]
  Proceedings of the 2nd workshop on NLP for Internet Freedom
  ( NLP4IF ): Censorship, Disinformation and Propaganda. EMNLP 2019.
  [ code ] [ data ] [ poster ] [ BibTeX ]

• Where is your Evidence: Improving Fact-checking by Justification Modeling
  Tariq Alhindi, Savvas Petridis, and Smaranda Muresan
  Proceedings of the First Workshop on Fact Extraction and Verification
  ( FEVER ), EMNLP 2018.
  [ data ] [ poster ] [ BibTeX ]

• Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification
  Tuhin Chakrabarty, Tariq Alhindi, and Smaranda Muresan
  [ ColumbiaNLP @leaderboard ]
  Proceedings of the First Workshop on Fact Extraction and Verification
  ( FEVER ), EMNLP 2018.
  [ code ] [ data ] [ poster ] [ BibTeX ]

Other Work

• Machine Generation and Detection of Arabic Manipulated and Fake News
  El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed, Tariq Alhindi, and Hasan Cavusoglu
  Proceedings of the 5th Arabic Natural Language Processing Workshop
  ( WANLP ), COLING 2020.
  [ data ] [ slides ] [ video ]
  [ BibTeX ]

• Spider-Jerusalem at SemEval-2019 Task 4: Hyperpartisan News Detection
  Amal Alabdulkarim, Tariq Alhindi
  [ Spider-Jerusalem @leaderboard ]
  Proceedings of the 13th International Workshop on Semantic Evaluation
  ( SemEval ), NAACL 2019.
  [ code ] [ data ] [ poster ] [ BibTeX ]

• A Multi-layer Annotated Corpus of Argumentative Text: From Argument Schemes to Discourse Relations
  Elena Musi, Tariq Alhindi, Manfred Stede, Leonard Kriese, Smaranda Muresan, and Andrea Rocci
  Proceedings of Language Resources and Evaluation Conference ( LREC ) 2018.
  [ slides ] [ BibTeX ]

News, Talks and Travel

• Talk at Columbia NLP Group on April 2022.
  Title: How can Argumentation Mining improve Misinformation Detection?

• Presented my summer internship project at Bloomberg AI. September 2021.
  Title: Retrofitted Transformers for Efficient Adversarial Attacks and Robust Sentiment Models

• Passed my Thesis Propsal Defense on June 2021.
  Title: Pragmatics-Infused Models for Argumentation and Misinformation Detection.

• Oral Presentation at BEA 2021 workshop at EACL (Online). April, 2021. [ slides ]

• Oral Presentation at COLING 2020 about Fact vs. Opinion detection in news. [ slides ] [ video ]

• Guest Speaker at the Demestifying the Dessertation Talk Series, CS Dept, Columbia University. March, 2021.
  Title: Applications of Argumentations Mining in News. [ slides ] [ video ]

• Summer Internship Project Presentation at ETS. August, 2020. [ slides ]
  Title: Claim Token Detection from Middle and High School Student Essays.

• Candidacy Exam Talk at the NLP group, CS Dept, Columbia University. March, 2020. [ slides ] [ list of papers ]
  Title: A Review of the Literature on Automatic Fact-Checking, Fake News Detection and Argumentation.

• Invited Talk at the WikiConference North America 2019 at MIT.
  [ slides ] [ abstract ]
  Title: Building, Breaking and Fixing Models for Fact-Checking. Cambridge, MA. Nov, 2019.

• Poster Talk at FEVER workshop. Justification modeling for fact-checking. Brussels, Belguim. Nov, 2018.

• Poster Talk at FEVER workshop. Our shared task system for fact-checking. Brussels, Belguim. Nov, 2018.

• Invited Talk at the NLP group, iSchool, University of British Columbia. Vancouver, Canada. August, 2018.
  [ slides ]

• Oral Presentation at LREC conference. Miyazaki, Japan. May, 2018. [ slides ]

Teaching

• Fall 2018: TA for COMS 4111: Introduction to Databases with Donald Ferguson

• Spring 2019: TA for COMS 4705: Natural Language Processing with Yassine Benajiba