128 citations · 215 across the 22 of their papers we have counts for
25 papers
Words Caught in the Heart: Simulating Person-Specific Expression for Self-Opaque Clients in Psychotherapy
Mengxi Xiao, Jingjing Chen, Ziyan Kuang +12
Psychotherapy clients may experience distress before they can coherently describe it, and their expression changes with emotion, perceived safety, and trust. Large language model-b…
Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation
Fengxian Ji, Yuke Li, Jingpu Yang +8
However, whether these judges truly evaluate the scientific substance of ideas or are influenced by superficial stylistic presentation remains an open question. To address this que…
LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents
Jingpu Yang, Fengxian Ji, Zhengzhao Lai +8
Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory environments remains challeng…
TVIR: Building Deep Research Agents Towards Text-Visual Interleaved Report Generation
Xinkai Ma, Zhiqi Bai, Dingling Zhang +21
Deep Research Agents have shown strong capability in multi-step information retrieval, reasoning, and long-form report generation, but existing benchmarks and systems remain predom…
Where Do Deep-Research Agents Go Wrong? Span-Level Error Localization in Agent Trajectories
Jiaming Wang, Ziteng Feng, Jiangtao Wu +8
Deep-research agents solve tasks through long trajectories of search, tool use, evidence inspection, and answer synthesis. Evaluation based on final answers shows whether an agent…
Overview of the ClinicalSkillQA 2026 Shared Task on Continuous Perception and Procedural Reasoning in Clinical Skill Assessment
Xiyang Huang, Renxiong Wei, Yihuai Xu +10
This paper presents an overview of the ClinicalSkillQA 2026 shared task, which was organized with the BioNLP Workshop at ACL 2026. The goal of this shared task is to evaluate conti…
TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice
Gang Hu, Yating Chen, Haiyan Ding +5
While Large Language Models (LLMs) excel in various general domains, they exhibit notable gaps in the highly specialized, knowledge-intensive, and legally regulated Chinese tax dom…
DR-Eval: Towards Realistic and Reproducible Deep Research Evaluation
Qianqian Xie, Qingheng Xiong, He Zhu +16
Deep Research Agents (DRAs) aim to solve complex, long-horizon research tasks involving planning, retrieval, multimodal understanding, and report generation, yet their evaluation r…
SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videos
Xiyang Huang, Jiawei Lin, Keying Wu +9
Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, temporal ordering, and long-context recall, but overlook a harder capability requi…
Appear2Meaning: A Cross-Cultural Benchmark for Structured Cultural Metadata Inference from Images
Yuechen Jiang, Enze Zhang, Md Mohsinul Kabir +4
Recent advances in vision-language models (VLMs) have improved image captioning for cultural heritage. However, inferring structured cultural metadata (e.g., creator, origin, perio…
MisSpans: Fine-Grained False Span Identification in Cross-Domain Fake News
Zhiwei Liu, Paul Thompson, Jiaqi Rong +5
Online misinformation is increasingly pervasive, yet most existing benchmarks and methods evaluate veracity at the level of whole claims or paragraphs using coarse binary labels, o…
RAAR: Retrieval Augmented Agentic Reasoning for Cross-Domain Misinformation Detection
Zhiwei Liu, Runteng Guo, Baojie Qu +4
Cross-domain misinformation detection is challenging, as misinformation arises across domains with substantial differences in knowledge and discourse. Existing methods often rely o…
MiraMind: Benchmarking Reliable Mental Health Reasoning beyond Answer Accuracy
Mengxi Xiao, Kailai Yang, Pengde Zhao +12
Mental-health reasoning with large language models (LLMs) is an evidence-constrained judgment problem: models must transform limited, subjective, and often ambiguous evidence into…
Plan Then Retrieve: Reinforcement Learning-Guided Complex Reasoning over Knowledge Graphs
Yanlin Song, Ben Liu, Víctor Gutiérrez-Basulto +5
Knowledge Graph Question Answering aims to answer natural language questions by reasoning over structured knowledge graphs. While large language models have advanced KGQA through t…
From Scores to Skills: A Cognitive Diagnosis Framework for Evaluating Financial Large Language Models
Ziyan Kuang, Feiyu Zhu, Maowei Jiang +8
Large Language Models (LLMs) have shown promise for financial applications, yet their suitability for this high-stakes domain remains largely unproven due to inadequacies in existi…
AgentMental: An Interactive Multi-Agent Framework for Explainable and Adaptive Mental Health Assessment
Jinpeng Hu, Ao Wang, Qianqian Xie +3
Mental health assessment is crucial for early intervention and effective treatment, yet traditional clinician-based approaches are limited by the shortage of qualified professional…
Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
Xueqing Peng, Triantafillos Papadopoulos, Efstathia Soufleri +7
Despite Greece's pivotal role in the global economy, large language models (LLMs) remain underexplored for Greek financial context due to the linguistic complexity of Greek and the…
FMDLlama: Financial Misinformation Detection based on Large Language Models
Zhiwei Liu, Xin Zhang, Kailai Yang +3
The emergence of social media has made the spread of misinformation easier. In the financial domain, the accuracy of information is crucial for various aspects of financial market,…
Are Large Language Models True Healthcare Jacks-of-All-Trades? Benchmarking Across Health Professions Beyond Physician Exams
Zheheng Luo, Chenhan Yuan, Qianqian Xie +1
Recent advancements in Large Language Models (LLMs) have demonstrated their potential in delivering accurate answers to questions about world knowledge. Despite this, existing benc…
RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Information
Zhiwei Liu, Kailai Yang, Qianqian Xie +3
Misinformation is prevalent in various fields such as education, politics, health, etc., causing significant harm to society. However, current methods for cross-domain misinformati…
MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models
Kailai Yang, Zhiwei Liu, Qianqian Xie +3
Recent advancements in large language models (LLMs) focus on aligning to heterogeneous human expectations and values via multi-objective preference alignment. However, existing met…
The Lay Person's Guide to Biomedicine: Orchestrating Large Language Models
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
Automated lay summarisation (LS) aims to simplify complex technical documents into a more accessible format to non-experts. Existing approaches using pre-trained language models, p…
Factual consistency evaluation of summarization in the Era of large language models
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
Factual inconsistency with source documents in automatically generated summaries can lead to misinformation or pose risks. Existing factual consistency (FC) metrics are constrained…
EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis
Zhiwei Liu, Kailai Yang, Tianlin Zhang +2
Sentiment analysis and emotion detection are important research topics in natural language processing (NLP) and benefit many downstream tasks. With the widespread application of LL…