21 citations · 46 across the 19 of their papers we have counts for
19 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…
FinCUABuild: Can Agents Build Reliable Benchmarks for Dynamic Financial Computer Use?
Jingpu Yang, Fengxian Ji, Jinri Guo +7
Financial scenarios are diverse and complex, spanning varying data conditions, tool configurations, and workflows. Yet existing CUA, Computer-Using Agent, evaluation tasks remain l…
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…
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…
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…
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…
Credibility Governance: A Social Mechanism for Collective Self-Correction under Weak Truth Signals
Wanying He, Yanxi Lin, Ziheng Zhou +5
Online platforms increasingly rely on opinion aggregation to allocate real-world attention and resources, yet common signals such as engagement votes or capital-weighted commitment…
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…
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…
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…
MoodAngels: A Retrieval-augmented Multi-agent Framework for Psychiatry Diagnosis
Mengxi Xiao, Ben Liu, He Li +5
The application of AI in psychiatric diagnosis faces significant challenges, including the subjective nature of mental health assessments, symptom overlap across disorders, and pri…
Retrieval-augmented Large Language Models for Financial Time Series Forecasting
Mengxi Xiao, Zihao Jiang, Lingfei Qian +10
Accurately forecasting stock price movements is critical for informed financial decision-making, supporting applications ranging from algorithmic trading to risk management. Howeve…
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Jimin Huang, Mengxi Xiao, Dong Li +41
Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…
No Language is an Island: Unifying Chinese and English in Financial Large Language Models, Instruction Data, and Benchmarks
Gang Hu, Ke Qin, Chenhan Yuan +6
While the progression of Large Language Models (LLMs) has notably propelled financial analysis, their application has largely been confined to singular language realms, leaving unt…
HealMe: Harnessing Cognitive Reframing in Large Language Models for Psychotherapy
Mengxi Xiao, Qianqian Xie, Ziyan Kuang +5
Large Language Models (LLMs) can play a vital role in psychotherapy by adeptly handling the crucial task of cognitive reframing and overcoming challenges such as shame, distrust, t…
Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English
Xiao Zhang, Ruoyu Xiang, Chenhan Yuan +8
Despite Spanish's pivotal role in the global finance industry, a pronounced gap exists in Spanish financial natural language processing (NLP) and application studies compared to En…
FinBen: A Holistic Financial Benchmark for Large Language Models
Qianqian Xie, Weiguang Han, Zhengyu Chen +31
LLMs have transformed NLP and shown promise in various fields, yet their potential in finance is underexplored due to a lack of comprehensive evaluation benchmarks, the rapid devel…