most citedNOMAD: A Multi-Agent LLM System for UML Class Diagram Generation from Natural Language Requirements

2 citations · 3 across the 20 of their papers we have counts for

collaborators

22 papers

cs.HC2026

One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spread

Zhuoran Lu, Weilong Wang, Yangyang Yu +4

Social media platforms increasingly use AI-based credibility indicators to help users judge misinformation. Unlike individual human-AI decision-making, these indicators are embedde…

cs.CL2026

NTDH: Complex Reasoning for Comprehensive Affective Analysis

Tianlei Zhu, Zhiwei Liu, Yuyan Wang +2

Comprehensive affective analysis is challenging for two reasons: it spans heterogeneous prediction tasks with continuous, ordinal, and multi-label outputs, and affective meaning is…

cs.CL2026

Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction

Hanhua Hong, Yizhi Li, Jiaoyan Chen +4

Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, where direct paper-to-repositor…

cs.CL2026

Janus: A Benchmark for Goal-Conditioned Information Distortion in LLMs

Polydoros Giannouris, Mohsinul Kabir, Sophia Ananiadou

LLM deception is often evaluated through direct markers such as fabricated claims, explicit lies, or strategic concealment. However, many real-world misleading communications do no…

cs.CE2026

AuditFraudBench: Benchmarking Audit Judgment in Detecting Fraudulent Misstatements

Zhiwei Liu, Yueru He, Qing Ou +4

Large language models (LLMs) have shown strong performance in financial analysis and surface-level factual error detection, yet their ability to identify fraudulent financial misin…

cs.AI2026

Herculean: An Agentic Benchmark for Financial Intelligence

Xueqing Peng, Zhuohan Xie, Yupeng Cao +60

As AI agents improve, the central question is no longer whether they can solve isolated well-defined financial tasks, but whether they can reliably carry out financial professional…