Papers by Khalid Al Khatib
Employing Argumentation Knowledge Graphs for Neural Argument Generation (2021.acl-long)
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| Challenge: | Existing methods for generating arguments use end-to-end knowledge graphs or are controlled with respect to the argument's topic, aspects, or stance. |
| Approach: | They construct and populate three knowledge graphs and encode them into debate portals and relevant paragraphs from Wikipedia. |
| Outcome: | The proposed model produces arguments with superior quality than those generated without knowledge. |
Detecting Media Bias in News Articles using Gaussian Bias Distributions (2020.findings-emnlp)
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| Challenge: | a new study shows that media bias is not only about honesty or accuracy, but also about taste or preference. |
| Approach: | They propose to use second-order information to detect media bias in articles . they propose to analyze the frequency, positions, and sequential order of biased statements . |
| Outcome: | The proposed model outperforms other models that use second-order information on biased statements on an existing media bias dataset. |
Generating Informative Conclusions for Argumentative Texts (2021.findings-acl)
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| Challenge: | Argumentative texts often omit explicit conclusions, expecting readers to infer them rather . a corpus of 136,996 arguments is compiled and used to generate informative conclusions . |
| Approach: | They propose to generate informative conclusions from a large-scale corpus of argumentative texts . they propose to use argumentative knowledge to augment the corpus and refine the model . |
| Outcome: | The proposed corpus of argumentative texts and their conclusions is compiled and analyzed . the results show that the proposed model is informative and concise . |
Controlled Neural Sentence-Level Reframing of News Articles (2021.findings-emnlp)
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| Challenge: | a news article is framed from a specific perspective, but reframing can be difficult . a framed article can be used to communicate with opposing camps of audiences . |
| Approach: | They propose to reframe news articles using a media frame corpus to achieve this . they propose three strategies to train neural models for reframing . |
| Outcome: | The proposed techniques maintain coherence of sentences and reframe them correctly . the proposed techniques are effective but have tradeoffs . |
Analyzing the Persuasive Effect of Style in News Editorial Argumentation (2020.acl-main)
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| Challenge: | Existing research has investigated the persuasive effect of content and style on argumentative content. |
| Approach: | They compare the style of news editorials with ideology-specific effect annotations to find out how important it is to achieve persuasiveness. |
| Outcome: | The proposed method shows that conservative readers are resistant to style on liberal editorials, whereas conservative readers resist style on conservatives. |
Summary Explorer: Visualizing the State of the Art in Text Summarization (2021.emnlp-demo)
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| Challenge: | Automatic text summarization is the task of generating a summary of a long text by condensing it to its most important parts. |
| Approach: | They propose a tool to visually explore document summarization systems based on three well-known summary quality criteria . |
| Outcome: | The proposed tool compiles outputs of 55 state-of-the-art document summarization approaches and visually explores them during a qualitative assessment. |
Differential Bias: On the Perceptibility of Stance Imbalance in Argumentation (2022.findings-aacl)
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| Challenge: | a theoretical model of bias classification is not feasible because of complexity of interpreting language phenomena. |
| Approach: | They propose to analyze whether a text is biased based on an algorithmic analysis . they propose to use a model to determine whether x is more biased than y . |
| Outcome: | a crowdsourcing study shows that differences in stance bias are perceptible when (light) support is provided through training or visual aids. |
Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition (D19-50)
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| Challenge: | Existing methods to detect abusive language only train one classifier for the whole variety of offending . a new method can support a moderator with explicit unraveled explanations for why something was flagged as abusive . |
| Approach: | a new method is proposed to distinguish explicitly abusive cases from the more "shadowed" ones . the researchers extend a lexicon of abusive terms to include new obfuscations of abusive words . |
| Outcome: | a new method can distinguish explicitly abusive cases from the more "shadowed" ones . the method can support a moderator with explicit unraveled explanations for why something was flagged as abusive . |
Reference-guided Style-Consistent Content Transfer (2024.lrec-main)
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| Challenge: | Text style transfer involves changing the style of a text while preserving its original style. |
| Approach: | They propose a task of style-consistent content transfer which involves modifying a text’s content based on a provided reference statement while preserving its original style. |
| Outcome: | The proposed approach meets three important conditions: reference faithfulness, style adherence, and coherence. |
Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness (2020.acl-main)
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| Challenge: | Several studies have examined persuasiveness in debates by probing the main factors for establishing persuasion, particularly regarding the role of linguistic features of debaters' arguments. |
| Approach: | They propose to model debaters’ prior beliefs, interests, and personality traits based on their previous activity without dependence on explicit user profiles or questionnaires. |
| Outcome: | The proposed model improves persuasiveness prediction and debater resistance to persuasion. |
Crawling and Preprocessing Mailing Lists At Scale for Dialog Analysis (2020.acl-main)
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| Challenge: | a new neural segmentation model is used to segment 153 million emails . email is perhaps the most reliable and ubiquitous means of digital communication . |
| Approach: | They present a new neural segmentation model that crawls 153 million emails . it achieves 96% accuracy on 15 classes of email segments . |
| Outcome: | The proposed model achieves state-of-the-art performance while being more efficient to train than previous ones. |
News Editorials: Towards Summarizing Long Argumentative Texts (2020.coling-main)
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| Challenge: | Using news summarization, we aim to target opinionated articles with a well-defined argumentation structure. |
| Approach: | They present a corpus of carefully curated summaries for 266 news editorials. |
| Outcome: | The summarization of opinionated articles with a well-defined argumentation structure is evaluated using a tailored annotation scheme. |
TL;DR Progress: Multi-faceted Literature Exploration in Text Summarization (2024.eacl-demo)
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| Challenge: | TL;DR Progress is a literature explorer designed specifically for the text summarization literature. |
| Approach: | They propose to organize 514 papers based on a comprehensive annotation scheme for text summarization approaches and a fine-grained, faceted search. |
| Outcome: | The proposed tool organizes 514papers based on a comprehensive annotation scheme for text summarization approaches and enables fine-grained, faceted search. |
Analyzing Persuasion Strategies of Debaters on Social Media (2022.coling-1)
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| Challenge: | Existing studies on the analysis of persuasion in online discussions focus on the effectiveness of comments in individual discussions and ignore the effectiveness analysis of debaters over multiple discussions. |
| Approach: | They propose to quantify debaters effectiveness in the online discussion platform "ChangeMyView" they aim to explore diverse insights into their persuasion strategies . |
| Outcome: | The proposed analysis of debater effectiveness in the ChangeMyView subreddit reveals that debaters have different levels of effectiveness, behavioral characteristics and text stylistic features . |