Papers by Dimitar Dimitrov
MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets (2021.findings-emnlp)
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Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, Md. Shad Akhtar, Preslav Nakov, Tanmoy Chakraborty
| Challenge: | a growing number of harmful memes are being used for trolling, cyberbullying and abuse . a new approach to detect harmful meme images and texts is emerging . |
| Approach: | They propose a multimodal deep neural network that detects harmful memes . they extend the recently released HarMeme dataset with additional memes and a new topic . |
| Outcome: | The proposed framework outperforms rival methods in detecting harmful memes and their target social entities. |
Dissecting Paraphrases: The Impact of Prompt Syntax and supplementary Information on Knowledge Retrieval from Pretrained Language Models (2024.naacl-long)
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| Challenge: | Pre-trained language models contain various kinds of knowledge. |
| Approach: | They designed a probe that allows comparison of 34 million distinct paraphrases that follow a unified meta-template enabling the controlled variation of syntax and semantics across arbitrary relations. |
| Outcome: | Extensive knowledge retrieval experiments show that prompts following clausal syntax have several desirable properties in comparison to appositive syntax. |
Detecting Propaganda Techniques in Memes (2021.acl-long)
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Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, Firoj Alam, Fabrizio Silvestri, Hamed Firooz, Preslav Nakov, Giovanni Da San Martino
| Challenge: | Propaganda can be defined as a form of communication that aims to influence opinions or the actions of people towards a specific goal. |
| Approach: | They propose to detect the type of propaganda techniques used in memes by annotating them with 22 techniques. |
| Outcome: | The proposed model identifies 22 propaganda techniques in memes, which can appear in text, image or both . |
EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models (2024.acl-long)
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| Challenge: | Existing benchmarks for vision language models are outdated and unable to accurately assess their performance. |
| Approach: | They propose a multi-discipline multimodal multilingual exam benchmark for vision language models . they collect multiple-choice questions across 20 disciplines across 11 languages from 7 language families . |
| Outcome: | The EXAMS-V exam includes 20,932 multiple-choice questions across 20 disciplines . the questions come in 11 languages from 7 language families and require advanced reasoning skills . |
Detecting Harmful Memes and Their Targets (2021.findings-acl)
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Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, Shivam Sharma, Md. Shad Akhtar, Preslav Nakov, Tanmoy Chakraborty
| Challenge: | a growing body of research on meme analysis has focused on detecting harmful memes and their social entities . a meme is a form of content that is often harmless and designed to look funny . but its multimodal nature and camouflaged semantics make its analysis challenging . |
| Approach: | They propose to use multimodal models to detect harmful memes and identify social entities that harmful meme targets. |
| Outcome: | The proposed model can detect harmful memes and the social entities they target . the proposed model lacks the appropriate contexts and is poorly validated . |