activity
20212026
most citedActive PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training

1 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

UXBench: Benchmarking User Experience in AI Assistants

Mengze Hong, Xia Zeng, Zeyang Lei +27

As AI assistants serve millions of users daily, evaluating user experience (UX) beyond general model capability has become increasingly important. We present \textbf{UXBench}, the…

cs.LG2026

ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs

Xianlin Zeng, Fan Xia, Xiangyu Chen

Text-attributed Graphs (TAGs) incorporate textual node attributes with graph structures to describe rich relational semantics. Recent efforts to integrate Graph Neural Networks (GN…

cs.CL2024★ 1 cited

MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification

Xia Zeng, Arkaitz Zubiaga

Claim verification is an essential step in the automated fact-checking pipeline which assesses the veracity of a claim against a piece of evidence. In this work, we explore the pot…

cs.CL2022★ 1 cited

Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training

Xia Zeng, Arkaitz Zubiaga

To mitigate the impact of the scarcity of labelled data on fact-checking systems, we focus on few-shot claim verification. Despite recent work on few-shot classification by proposi…

cs.CL2022★ 1 cited

Aggregating Pairwise Semantic Differences for Few-Shot Claim Veracity Classification

Xia Zeng, Arkaitz Zubiaga

As part of an automated fact-checking pipeline, the claim veracity classification task consists in determining if a claim is supported by an associated piece of evidence. The compl…

cs.CL2021

Automated Fact-Checking: A Survey

Xia Zeng, Amani S. Abumansour, Arkaitz Zubiaga

As online false information continues to grow, automated fact-checking has gained an increasing amount of attention in recent years. Researchers in the field of Natural Language Pr…

cs.CL2021

QMUL-SDS at SCIVER: Step-by-Step Binary Classification for Scientific Claim Verification

Xia Zeng, Arkaitz Zubiaga

Scientific claim verification is a unique challenge that is attracting increasing interest. The SCIVER shared task offers a benchmark scenario to test and compare claim verificatio…