1 citations · 1 across the 12 of their papers we have counts for
14 papers
TransMeme: A Multi-Agent Framework for Cross-Cultural Meme Transcreation
Jingyi Zheng, Yule Liu, Zifan Peng +4
Internet memes are a pervasive form of multimodal online communication; however, such communication often involves users from diverse linguistic and cultural backgrounds. Therefore…
AtomEval: Validity-Aware Atomic Evaluation of Adversarial Claim Rewriting in Fact Verification
Hongyi Cen, Mingxin Wang, Yule Liu +3
Large language models (LLMs) can rewrite refuted claims to evade evidence-based fact verifiers, but conventional attack success rate (ASR) can be inflated when rewrites change, wea…
Localization Boosting for Growth Markets: Mitigating Cross-Locale Behavioral Bias in Learning-to-Rank
Suryaa Veerabathiran Seran, Ashwin Naresh Kumar, Tracy Holloway King +1
Adobe Express is expanding internationally, but the US has a disproportionately large content supply and interaction volume. Learning-to-rank (LTR) models trained primarily on beha…
On the Generation and Mitigation of Harmful Geometry in Image-to-3D Models
Yule Liu, Yilong Yang, Jiale Teng +11
Recent advances in image-to-3D models have significantly improved the fidelity and accessibility of 3D content creation. Such a powerful reconstruction capability that enables crea…
CHASM: Unveiling Covert Advertisements on Chinese Social Media
Jingyi Zheng, Tianyi Hu, Yule Liu +5
Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements, which disguise themselves as…
TxSum: User-Centered Ethereum Transaction Understanding with Micro-Level Semantic Grounding
Zifan Peng, Jingyi Zheng, Yule Liu +8
Understanding the economic intent of Ethereum transactions is critical for user safety, yet current tools expose only raw on-chain data or surface-level intent, leading to widespre…
ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
Wenhan Dong, Zhen Sun, Yuemeng Zhao +9
Large language models (LLMs) have demonstrated potential in educational applications, yet their capacity to accurately assess the cognitive alignment of reading materials with stud…
GasAgent: A Multi-Agent Framework for Automated Gas Optimization in Smart Contracts
Jingyi Zheng, Zifan Peng, Yule Liu +4
Smart contracts are trustworthy, immutable, and automatically executed programs on the blockchain. Their execution requires the Gas mechanism to ensure efficiency and fairness. How…
Evaluation Hallucination in Multi-Round Incomplete Information Lateral-Driven Reasoning Tasks
Wenhan Dong, Tianyi Hu, Jingyi Zheng +5
Multi-round incomplete information tasks are crucial for evaluating the lateral thinking capabilities of large language models (LLMs). Currently, research primarily relies on multi…
JALMBench: Benchmarking Jailbreak Vulnerabilities in Audio Language Models
Zifan Peng, Yule Liu, Zhen Sun +9
Large Audio Language Models (LALMs) have made significant progress. While increasingly deployed in real-world applications, LALMs face growing safety risks from jailbreak attacks t…
Humanizing LLMs: A Survey of Psychological Measurements with Tools, Datasets, and Human-Agent Applications
Wenhan Dong, Yuemeng Zhao, Zhen Sun +10
As large language models (LLMs) are increasingly used in human-centered tasks, assessing their psychological traits is crucial for understanding their social impact and ensuring tr…
Thought Manipulation: External Thought Can Be Efficient for Large Reasoning Models
Yule Liu, Jingyi Zheng, Zhen Sun +6
Recent advancements in large reasoning models (LRMs) have demonstrated the effectiveness of scaling test-time computation to enhance reasoning capabilities on various tasks. Howeve…
TH-Bench: Evaluating Evading Attacks via Humanizing AI Text on Machine-Generated Text Detectors
Jingyi Zheng, Junfeng Wang, Zhen Sun +3
As Large Language Models (LLMs) advance, Machine-Generated Texts (MGTs) have become increasingly fluent, high-quality, and informative. Existing wide-range MGT detectors are design…
Unsafe LLM-Based Search: Quantitative Analysis and Mitigation of Safety Risks in AI Web Search
Zeren Luo, Zifan Peng, Yule Liu +4
Recent advancements in Large Language Models (LLMs) have significantly enhanced the capabilities of AI-Powered Search Engines (AIPSEs), offering precise and efficient responses by…