Papers by Oana Balalau
Discovering the Functions of Language in Online Forums (D19-55)
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| Challenge: | a vast amount of work has been dedicated to speech act categorization for characterizing discourses . lack of formalism and diversity of taxonomies make it difficult to compare different annotated datasets. |
| Approach: | They propose a semi-supervised framework for predicting the functions of Reddit comments . they propose to use the framework to analyze online forum conversations . |
| Outcome: | The proposed framework can predict functions of Reddit comments and 165K comments. |
Structured Discourse Representation for Factual Consistency Verification (2025.findings-acl)
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| Challenge: | Existing methods to verify factual consistency of text capture a performance gap compared with sentence-level entailment. |
| Approach: | They propose a method that combines structured discourse information extraction with a classifier, FDSpotter, for factual consistency verification. |
| Outcome: | The proposed method achieves competitive performance on two tasks: data-to-text generation and text summarisation. |
FactSpotter: Evaluating the Factual Faithfulness of Graph-to-Text Generation (2023.findings-emnlp)
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| Challenge: | Graph-to-text (G2T) generation is an important task in natural language generation as it renders graphs accessible to non-technical users in downstream applications such as question answering. |
| Approach: | They propose a metric that correctly identifies factual faithfulness and uses it to determine if a triple is present in a generated text. |
| Outcome: | The proposed metric achieves highest correlation with human annotations on data correctness, data coverage, and relevance. |
The Search for Conflicts of Interest: Open Information Extraction in Scientific Publications (2025.findings-emnlp)
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| Challenge: | public repositories of relations of interest are increasingly recommended or mandated in various domains to avoid COIs. |
| Approach: | They propose an LLM-based open information extraction framework for extracting financial or other types of interesting relations from scientific text. |
| Outcome: | The proposed framework extracts financial or other types of interesting relations from scientific text. |
From the Stage to the Audience: Propaganda on Reddit (2021.eacl-main)
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| Challenge: | a recent opinion piece in the Washington Post highlights a difference between the political discourse in the two countries. |
| Approach: | They analyze political forums on Reddit that target a diverse audience in two countries . they focus on three research questions: who is posting propaganda? and how is propaganda received? |
| Outcome: | The authors analyze political forums on reddit in the US and the UK for one year . they find that propaganda is misleading and is received by different audiences . |
Navigating the Political Compass: Evaluating Multilingual LLMs across Languages and Nationalities (2025.findings-acl)
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| Challenge: | Large Language Models (LLMs) are ubiquitous in today’s technological landscape, boasting a plethora of applications, and even endangering human jobs in complex and creative fields. |
| Approach: | They evaluate the political bias of 15 multilingual LLMs using the Political Compass Test and assign a nationality to each model. |
| Outcome: | The models on the 50 most populous countries and their official languages exhibit political bias. |
Breaking Down the Invisible Wall of Informal Fallacies in Online Discussions (2021.acl-long)
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| Challenge: | a number of people engage in unsound argumentation techniques to prove a claim on online platforms . fallacies are weak arguments that seem convincing, but their evidence does not prove or disprove the conclusion . |
| Approach: | They propose to use user comments containing fallacy mentions as noisy labels to classify fallacies . they use the pragma-dialectical theory of argumentation to study the most common fallacias on Reddit . |
| Outcome: | The proposed dataset of fallacies on reddit shows that neural models perform better in conversational context. |
Open Information Extraction with Entity Focused Constraints (2023.findings-eacl)
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| Challenge: | Open Information Extraction (OIE) is the task of extracting tuples from unstructured corpora without any knowledge of the type and lexical form of the subject, the object, or the subject. |
| Approach: | They exploit domain knowledge to inject constraints into the extraction through constrained inference and constraint-aware training. |
| Outcome: | The proposed approach improves the CaRB and WIRe57 metric and achieves a 29.17% improvement in the CARB and 24.37% improvement on the WIRe56 metric. |
Benchmarking the Benchmarks: Reproducing Climate-Related NLP Tasks (2025.findings-acl)
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| Challenge: | a recent study examines the use of climate-related natural language processing (NLP) for climate-relevant tasks. |
| Approach: | They perform a reproducibility study on 8 tasks and 29 datasets, testing 6 models. |
| Outcome: | The proposed models are based on 8 tasks and 29 datasets. |