activity
20242026
most citedFactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data Pruning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Memory Echo in Single-Agent Long-Term Memory: Lifecycle Evaluation and Provenance-Guided Mitigation

Yufeng Li, Sheng Yao, Peng Zeng +5

Long-term memory supports agents across sessions. Repeated retrieval and write-back can let one historical claim occupy multiple retrieval positions and influence current answers w…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024★ 1 cited

FactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data Pruning

Yufeng Li, Rrubaa Panchendrarajan, Arkaitz Zubiaga

The rapid dissemination of information through social media and the Internet has posed a significant challenge for fact-checking, among others in identifying check-worthy claims th…