Papers by Daniel Russo
Countering Misinformation via Emotional Response Generation (2023.emnlp-main)
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| Challenge: | Social media platforms (SMPs) are one of the most effective ways to spread misinformation by engaging in constructive dialogue with users who spread – often in good faith – misleading messages. |
| Approach: | They propose to use social correction to engage in constructive dialogue with users who spread misleading messages. |
| Outcome: | The proposed dataset shows that it improves on previous studies on claim-response pairs and the author-reviewer pipeline. |
NLP for Counterspeech against Hate and Misinformation (CSHAM) (2025.acl-tutorials)
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| Challenge: | tutorial aims to show how counterspeech is used to tackle abuse and misinformation by individuals, activists and organisations. |
| Approach: | tutorial aims to show how counterspeech is currently used to tackle abuse and misinformation . will also show how Natural Language Processing (NLP) and Generation (NLG) can be applied to automate its production. |
| Outcome: | The tutorial will bring diverse multidisciplinary perspectives to safety research . case studies from industry and public policy will be included . |
LitBench: A Benchmark and Dataset for Reliable Evaluation of Creative Writing (2026.eacl-long)
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| Challenge: | a single prompt can inspire countless valid stories, making objective verification impossible. |
| Approach: | They propose a large-scale benchmark for creative writing evaluation using a reddit corpus and a 2,480-pair test set. |
| Outcome: | The proposed model outperforms existing OTS judges and generative reward models in the evaluation of creative writing. |
EuroVerdict: A Multilingual Dataset for Verdict Generation Against Misinformation (2025.findings-acl)
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| Challenge: | a global issue that shapes public discourse shapes opinion and decision-making . many multilingual work has focused on claim verification rather than generating explanatory verdicts . |
| Approach: | They propose a multilingual dataset designed for verdict generation covering eight European languages. |
| Outcome: | The EuroVerdict dataset covers claims, manual verdicts, and supporting evidence . it is compared with other datasets in eight European languages . |
Benchmarking the Generation of Fact Checking Explanations (2023.tacl-1)
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| Challenge: | Automating fact-checking is a time-consuming task that cannot keep up with the ever-increasing amount of fake news produced daily. |
| Approach: | They propose to automate the process of fact-checking by generating justifications from textual explanations of why a claim is classified as either true or false. |
| Outcome: | The proposed approach improves summarization performance over unstructured knowledge and with two datasets with different styles and structures. |
First-AID: the first Annotation Interface for grounded Dialogues (2025.acl-demo)
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| Challenge: | Existing tools to fine-tune Large Language Models for specific tasks are limited due to financial constraints and limited availability of human experts. |
| Approach: | They propose a human-in-the-loop framework for the knowledge-driven generation of synthetic dialogues using LLM prompting that implements different strategies of data collection that require different user intervention during dialogue generation. |
| Outcome: | The proposed framework reduces post-editing efforts and improves quality of generated dialogues. |