Supervised Multimodal Bitransformers for Classifying Images and Text. - Douwe Kiela; Suvrat Bhooshan; Hamed Firooz; Davide Testuggine (ViGIL@NeurIPS, 2019)

The Hateful Memes Challenge: Competition Report. - Douwe Kiela; Hamed Firooz; Aravind Mohan; Vedanuj Goswami; Amanpreet Singh; Casey A. Fitzpatrick; Peter Bull; Greg Lipstein; Tony Nelli; Ron Zhu; Niklas Muennighoff; Riza Velioglu; et al. (NeurIPS (Competition and Demos), 2020)

The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes. - Douwe Kiela; Hamed Firooz; Aravind Mohan; Vedanuj Goswami; Amanpreet Singh; Pratik Ringshia; Davide Testuggine (NeurIPS, 2020)

Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption. - Ivan Evtimov; Russ Howes; Brian Dolhansky; Hamed Firooz; Cristian Canton-Ferrer (CoRR, 2020)

Detecting Propaganda Techniques in Memes. - Dimitar Dimitrov 003; Bishr Bin Ali; Shaden Shaar; Firoj Alam; Fabrizio Silvestri; Hamed Firooz; Preslav Nakov; Giovanni Da San Martino (ACL/IJCNLP (1), 2021)

MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding. - Woojeong Jin 001; Maziar Sanjabi; Shaoliang Nie; Liang Tan 005; Xiang Ren 001; Hamed Firooz (EMNLP (Findings), 2021)

SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images. - Dimitar Dimitrov 003; Bishr Bin Ali; Shaden Shaar; Firoj Alam; Fabrizio Silvestri; Hamed Firooz; Preslav Nakov; Giovanni Da San Martino (SemEval@ACL/IJCNLP, 2021)

Modality-specific Distillation. - Woojeong Jin 001; Maziar Sanjabi; Shaoliang Nie; Liang Tan 005; Xiang Ren 001; Hamed Firooz (CoRR, 2021)

A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision. - Ajinkya Tejankar; Maziar Sanjabi; Bichen Wu; Saining Xie; Madian Khabsa; Hamed Pirsiavash; Hamed Firooz (CoRR, 2021)

Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem. - Khalil Mrini; Shaoliang Nie; Jiatao Gu; Sinong Wang; Maziar Sanjabi; Hamed Firooz (ACL (Findings), 2022)

A Survey on Multimodal Disinformation Detection. - Firoj Alam; Stefano Cresci; Tanmoy Chakraborty 002; Fabrizio Silvestri; Dimiter Dimitrov; Giovanni Da San Martino; Shaden Shaar; Hamed Firooz; Preslav Nakov (COLING, 2022)

ER-Test: Evaluating Explanation Regularization Methods for Language Models. - Brihi Joshi; Aaron Chan; Ziyi Liu 007; Shaoliang Nie; Maziar Sanjabi; Hamed Firooz; Xiang Ren 001 (EMNLP (Findings), 2022)

UNIREX: A Unified Learning Framework for Language Model Rationale Extraction. - Aaron Chan; Maziar Sanjabi; Lambert Mathias; Liang Tan 005; Shaoliang Nie; Xiaochang Peng; Xiang Ren 001; Hamed Firooz (ICML, 2022)

Detecting and Understanding Harmful Memes: A Survey. - Shivam Sharma; Firoj Alam; Md. Shad Akhtar; Dimitar Dimitrov 003; Giovanni Da San Martino; Hamed Firooz; Alon Y. Halevy; Fabrizio Silvestri; Preslav Nakov; Tanmoy Chakraborty 002 (IJCAI, 2022)

BARACK: Partially Supervised Group Robustness With Guarantees. - Nimit Sharad Sohoni; Maziar Sanjabi; Nicolas Ballas; Aditya Grover; Shaoliang Nie; Hamed Firooz; Christopher Ré (CoRR, 2022)

Understanding Failure Modes of Self-Supervised Learning. - Neha Mukund Kalibhat; Kanika Narang; Liang Tan 005; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (CoRR, 2022)

ER-TEST: Evaluating Explanation Regularization Methods for NLP Models. - Brihi Joshi; Aaron Chan; Ziyi Liu 007; Shaoliang Nie; Maziar Sanjabi; Hamed Firooz; Xiang Ren 001 (CoRR, 2022)

FRAME: Evaluating Simulatability Metrics for Free-Text Rationales. - Aaron Chan; Shaoliang Nie; Liang Tan 005; Xiaochang Peng; Hamed Firooz; Maziar Sanjabi; Xiang Ren 001 (CoRR, 2022)

Meta-training with Demonstration Retrieval for Efficient Few-shot Learning. - Aaron Mueller; Kanika Narang; Lambert Mathias; Qifan Wang 001; Hamed Firooz (ACL (Findings), 2023)

MUSTIE: Multimodal Structural Transformer for Web Information Extraction. - Qifan Wang 001; Jingang Wang; Xiaojun Quan; Fuli Feng; Zenglin Xu; Shaoliang Nie; Sinong Wang; Madian Khabsa; Hamed Firooz; Dongfang Liu (ACL (1), 2023)

Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning. - Ajinkya Tejankar; Maziar Sanjabi; Qifan Wang 001; Sinong Wang; Hamed Firooz; Hamed Pirsiavash; Liang Tan 005 (CVPR, 2023)

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation. - Nan Wang; Qifan Wang 001; Yi-Chia Wang; Maziar Sanjabi; Jingzhou Liu; Hamed Firooz; Hongning Wang; Shaoliang Nie (EMNLP, 2023)

Identifying Interpretable Subspaces in Image Representations. - Neha Mukund Kalibhat; Shweta Bhardwaj; C. Bayan Bruss; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (ICML, 2023)

Understanding the detrimental class-level effects of data augmentation. - Polina Kirichenko; Mark Ibrahim; Randall Balestriero; Diane Bouchacourt; Shanmukha Ramakrishna Vedantam; Hamed Firooz; Andrew Gordon Wilson (NeurIPS, 2023)

Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features. - Neha Mukund Kalibhat; Kanika Narang; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (AAAI, 2024)

RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. - Song Jiang 002; Zahra Shakeri; Aaron Chan; Maziar Sanjabi; Hamed Firooz; Yinglong Xia; Bugra Akyildiz; Yizhou Sun; Jinchao Li; Qifan Wang 001; Asli Celikyilmaz (NAACL-HLT, 2024)

Enhancing Stability for Large Models Training in Constrained Bandwidth Networks. - Yun Dai; Tejas Dharamsi; Byron Hsu; Tao Song; Hamed Firooz (CoRR, 2024)

Lost-in-Distance: Impact of Contextual Proximity on LLM Performance in Graph Tasks. - Hamed Firooz; Maziar Sanjabi; Wenlong Jiang; Xiaoling Zhai (CoRR, 2024)

CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations. - Vignesh Kothapalli; Hamed Firooz; Maziar Sanjabi (ACL (1), 2025)

360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation. - Hamed Firooz; Maziar Sanjabi; Adrian Englhardt; Aman Gupta; Ben Levine; Dre Olgiati; Gungor Polatkan; Iuliia Melnychuk; Karthik Ramgopal; Kirill Talanine; Kutta Srinivasan; Luke Simon; et al. (CoRR, 2025)

Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications. - Kayhan Behdin; Yun Dai; Ata Fatahi Baarzi; Aman Gupta; Qingquan Song; Shao Tang; Hejian Sang; Gregory Dexter; Sirou Zhu; Siyu Zhu; Tejas Dharamsi; Maziar Sanjabi; et al. (CoRR, 2025)

CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context Demonstrations. - Vignesh Kothapalli; Hamed Firooz; Maziar Sanjabi (CoRR, 2025)