739 citations · 2.4k across the 93 of their papers we have counts for
99 papers
THBKG: A Temporal Biomedical Knowledge Graph for Decision-Aligned Clinical Advancement Prediction
Pui Chung Siu, Claudia Cabrera, Mani Mudaliar +1
Inadequate target--disease linkage accounts for 40--50\% of Phase~II efficacy failures, so anticipating which programmes will advance would let sponsors back the hypotheses most li…
BiCon-Gate: Consistency-Gated De-colloquialisation for Dialogue Fact-Checking
Hyunkyung Park, Arkaitz Zubiaga
Automated fact-checking in dialogue involves multi-turn conversations where colloquial language is frequent yet understudied. To address this gap, we propose a conservative rewrite…
Claim2Vec: Embedding Fact-Check Claims for Multilingual Similarity and Clustering
Rrubaa Panchendrarajan, Arkaitz Zubiaga
Recurrent claims present a major challenge for automated fact-checking systems designed to combat misinformation, especially in multilingual settings. While tasks such as claim mat…
ContextClaim: A Context-Driven Paradigm for Verifiable Claim Detection
Yufeng Li, Rrubaa Panchendrarajan, Arkaitz Zubiaga
Automated fact-checking pipelines typically begin with a filtering stage that decides which claims are worth verifying, given that the later evidence retrieval and verification com…
NAU-QMUL: Utilizing BERT and CLIP for Multi-modal AI-Generated Image Detection
Xiaoyu Guo, Arkaitz Zubiaga
With the aim of detecting AI-generated images and identifying the specific models responsible for their generation, we propose a multi-modal multi-task model. The model leverages p…
MultiCaption: Detecting disinformation using multilingual visual claims
Rafael Martins Frade, Rrubaa Panchendrarajan, Arkaitz Zubiaga
Online disinformation poses an escalating threat to society, driven increasingly by the rapid spread of misleading content across both multimedia and multilingual platforms. While…
Agent-based Automated Claim Matching with Instruction-following LLMs
Dina Pisarevskaya, Arkaitz Zubiaga
We present a novel agent-based approach for the automated claim matching task with instruction-following LLMs. We propose a two-step pipeline that first generates prompts with LLMs…
ALHD: A Large-Scale and Multigenre Benchmark Dataset for Arabic LLM-Generated Text Detection
Ali Khairallah, Arkaitz Zubiaga
We introduce ALHD, the first large-scale comprehensive Arabic dataset explicitly designed to distinguish between human- and LLM-generated texts. ALHD spans three genres (news, soci…
Evolution of meta's llama models and parameter-efficient fine-tuning of large language models: a survey
Abdulhady Abas Abdullah, Arkaitz Zubiaga, Seyedali Mirjalili +5
This review surveys the rapid evolution of Meta AI's LLaMA (Large Language Model Meta AI) series - from LLaMA 1 through LLaMA 4 and the specialized parameter-efficient fine-tuning…
RAVE: Retrieval and Scoring Aware Verifiable Claim Detection
Yufeng Li, Arkaitz Zubiaga
The rapid spread of misinformation on social media underscores the need for scalable fact-checking tools. A key step is claim detection, which identifies statements that can be obj…
Towards Inclusive Toxic Content Moderation: Addressing Vulnerabilities to Adversarial Attacks in Toxicity Classifiers Tackling LLM-generated Content
Shaz Furniturewala, Arkaitz Zubiaga
Adversarial perturbations can reduce state-of-the-art toxicity classifiers to near-zero accuracy, yet existing defences treat models as black boxes. We apply mechanistic interpreta…
FineDialFact: A benchmark for Fine-grained Dialogue Fact Verification
Xiangyan Chen, Yufeng Li, Yujian Gan +2
Large language models are known to produce hallucinations - factually incorrect or fabricated information - which poses significant challenges for many natural language processing…
NLP for Social Good: A Survey and Outlook of Challenges, Opportunities, and Responsible Deployment
Antonia Karamolegkou, Angana Borah, Eunjung Cho +30
Natural language processing (NLP) now shapes many aspects of our world, yet its potential for positive social impact is underexplored. This paper surveys work in ``NLP for Social G…
MultiClaimNet: A Massively Multilingual Dataset of Fact-Checked Claim Clusters
Rrubaa Panchendrarajan, Rubén Míguez, Arkaitz Zubiaga
In the context of fact-checking, claims are often repeated across various platforms and in different languages, which can benefit from a process that reduces this redundancy. While…
Understanding the Effects of RLHF on the Quality and Detectability of LLM-Generated Texts
Beining Xu, Arkaitz Zubiaga
Large Language Models (LLMs) have demonstrated exceptional performance on a range of downstream NLP tasks by generating text that closely resembles human writing. However, the ease…
Will I Get Hate Speech Predicting the Volume of Abusive Replies before Posting in Social Media
Raneem Alharthi, Rajwa Alharthi, Ravi Shekhar +2
Despite the growing body of research tackling offensive language in social media, this research is predominantly reactive, determining if content already posted in social media is…
Entity-aware Cross-lingual Claim Detection for Automated Fact-checking
Rrubaa Panchendrarajan, Arkaitz Zubiaga
Identifying claims requiring verification is a critical task in automated fact-checking, especially given the proliferation of misinformation on social media platforms. Despite not…
Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking
Dina Pisarevskaya, Arkaitz Zubiaga
The claim matching (CM) task can benefit an automated fact-checking pipeline by putting together claims that can be resolved with the same fact-check. In this work, we are the firs…
ALPET: Active Few-shot Learning for Citation Worthiness Detection in Low-Resource Wikipedia Languages
Aida Halitaj, Arkaitz Zubiaga
Citation Worthiness Detection (CWD) consists in determining which sentences, within an article or collection, should be backed up with a citation to validate the information it pro…
Detecting harassment and defamation in cyberbullying with emotion-adaptive training
Peiling Yi, Arkaitz Zubiaga, Yunfei Long
Existing research on detecting cyberbullying incidents on social media has primarily concentrated on harassment and is typically approached as a binary classification task. However…
Supporting Automated Fact-checking across Topics: Similarity-driven Gradual Topic Learning for Claim Detection
Amani S. Abumansour, Arkaitz Zubiaga
Selecting check-worthy claims for fact-checking is considered a crucial part of expediting the fact-checking process by filtering out and ranking the check-worthy claims for being…
Understanding the Effects of Human-written Paraphrases in LLM-generated Text Detection
Hiu Ting Lau, Arkaitz Zubiaga
Natural Language Generation has been rapidly developing with the advent of large language models (LLMs). While their usage has sparked significant attention from the general public…
Cross-Target Stance Detection: A Survey of Techniques, Datasets, and Challenges
Parisa Jamadi Khiabani, Arkaitz Zubiaga
Stance detection is the task of determining the viewpoint expressed in a text towards a given target. A specific direction within the task focuses on cross-target stance detection,…
Applying the Ego Network Model to Cross-Target Stance Detection
Jack Tacchi, Parisa Jamadi Khiabani, Arkaitz Zubiaga +2
Understanding human interactions and social structures is an incredibly important task, especially in such an interconnected world. One task that facilitates this is Stance Detecti…