153 citations · 454 across the 53 of their papers we have counts for
54 papers
TimeLitmus: A Diagnostic Benchmark for Cross-Modal Understanding and Explanation Faithfulness in Event-Conditioned Time-Series Prediction
Jie Gong, Maowei Jiang, Zhiwei Liu +6
Large language models (LLMs) are increasingly used to make predictions from numerical time-series histories and textual events. Yet accuracy alone cannot reveal whether correct ans…
ShiJianBench: From Dialogue to Decision for Long-Horizon Evaluation of Investment Advisors
Jie Gong, Maowei Jiang, Zhiwei Liu +14
Conversational investment advisors influence not only what users know, but also how they make subsequent decisions as market conditions evolve. Existing evaluations primarily asses…
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…
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…
Ebisu: Benchmarking Large Language Models in Japanese Finance
Xueqing Peng, Ruoyu Xiang, Fan Zhang +9
Japanese finance combines agglutinative, head-final linguistic structure, mixed writing systems, and high-context communication norms that rely on indirect expression and implicit…
All That Glisters Is Not Gold: A Benchmark for Reference-Free Counterfactual Financial Misinformation Detection
Yuechen Jiang, Zhiwei Liu, Yupeng Cao +10
We introduce RFC Bench, a benchmark for evaluating large language models on financial misinformation under realistic news. RFC Bench operates at the paragraph level and captures th…
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…
Implicit Graph, Explicit Retrieval: Towards Efficient and Interpretable Long-horizon Memory for Large Language Models
Xin Zhang, Kailai Yang, Hao Li +3
Long-horizon applications increasingly require large language models (LLMs) to answer queries when relevant evidence is sparse and dispersed across very long contexts. Existing mem…
Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models
Hengyuan Zhang, Zhihao Zhang, Mingyang Wang +26
Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However, existing reviews primarily treat…
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…
When Agents Trade: Live Multi-Market Trading Benchmark for LLM Agents
Lingfei Qian, Xueqing Peng, Yan Wang +14
Although Large Language Model (LLM)-based agents are increasingly used in financial trading, it remains unclear whether they can reason and adapt in live markets, as most studies t…
Natural Language Processing for Cardiology: A Narrative Review
Kailai Yang, Yan Leng, Xin Zhang +5
Cardiovascular diseases are becoming increasingly prevalent in modern society, with a profound impact on global health and well-being. These Cardiovascular disorders are complex an…
DITING: A Multi-Agent Evaluation Framework for Benchmarking Web Novel Translation
Enze Zhang, Jiaying Wang, Mengxi Xiao +7
Large language models (LLMs) have substantially advanced machine translation (MT), yet their effectiveness in translating web novels remains unclear. Existing benchmarks rely on su…
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…
Exploring Safety Alignment Evaluation of LLMs in Chinese Mental Health Dialogues via LLM-as-Judge
Yunna Cai, Fan Wang, Haowei Wang +5
Evaluating the safety alignment of LLM responses in high-risk mental health dialogues is particularly difficult due to missing gold-standard answers and the ethically sensitive nat…
MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application
Xueqing Peng, Lingfei Qian, Yan Wang +44
Real-world financial analysis involves information across multiple languages and modalities, from reports and news to scanned filings and meeting recordings. Yet most existing eval…
MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs
Zhiwei Liu, Lingfei Qian, Qianqian Xie +3
Large language models and vision-language models (which we jointly call LMs) have transformed NLP and CV, demonstrating remarkable potential across various fields. However, their c…
Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs
Zeping Yu, Sophia Ananiadou
Although multimodal large language models (MLLMs) have achieved impressive performance, the multimodal instruction tuning stage often causes catastrophic forgetting of the base LLM…
ConspEmoLLM-v2: A robust and stable model to detect sentiment-transformed conspiracy theories
Zhiwei Liu, Paul Thompson, Jiaqi Rong +1
Despite the many benefits of large language models (LLMs), they can also cause harm, e.g., through automatic generation of misinformation, including conspiracy theories. Moreover,…
FinAudio: A Benchmark for Audio Large Language Models in Financial Applications
Yupeng Cao, Haohang Li, Yangyang Yu +10
Audio Large Language Models (AudioLLMs) have received widespread attention and have significantly improved performance on audio tasks such as conversation, audio understanding, and…
SynGraph: A Dynamic Graph-LLM Synthesis Framework for Sparse Streaming User Sentiment Modeling
Xin Zhang, Qiyu Wei, Yingjie Zhu +3
User reviews on e-commerce platforms exhibit dynamic sentiment patterns driven by temporal and contextual factors. Traditional sentiment analysis methods focus on static reviews, f…