1 citations · 2 across the 9 of their papers we have counts for
11 papers
AgentPrivArena: Evaluating and Auditing Real-world AI Agent Privacy
Shouju Wang, Haopeng Zhang
The rapid advancement of LLM agents has enabled systems to autonomously perform complex tasks through external tools, but their growing access to personal data introduces significa…
LoopArena: Benchmarking Models as Runtime Controllers for Loop Engineering
Yi Wang, Haopeng Zhang, Chengxiang Huang +4
Loop Engineering is emerging as a practice for organizing development work around coding agents. Instead of writing each prompt by hand, practitioners design loops that monitor pro…
Zero-Fi: Zero-Shot Wi-Fi-Based Human Activity Recognition via Contrastive Signal-Language Alignment
Yitong Shen, Cheng Guo, Peiliang Wang +5
Wi-Fi-based human activity recognition has advanced substantially, but most existing methods assume a closed set of activities and require labeled Wi-Fi samples for every target cl…
Position: Generative Engine Optimization Creates Underexamined Risks, Governance Must Target Concentration, Disclosure, and Academic Blind Spots
Yizhu Wen, Nan Zhang, Haohan Yuan +3
Large language model (LLM) answer engines are increasingly used for information seeking, shifting visibility from ranked lists to synthesized answers. This enables Generative Engin…
LLaTiSA: Towards Difficulty-Stratified Time Series Reasoning from Visual Perception to Semantics
Yueyang Ding, HaoPeng Zhang, Rui Dai +4
Comprehensive understanding of time series remains a significant challenge for Large Language Models (LLMs). Current research is hindered by fragmented task definitions and benchma…
Understanding LLM Reasoning for Abstractive Summarization
Haohan Yuan, Haopeng Zhang
Reasoning has substantially improved Large Language Models (LLMs) on analytical tasks such as mathematics and code generation, but its value for abstractive summarization remains u…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
StrucSum: Graph-Structured Reasoning for Long Document Extractive Summarization with LLMs
Haohan Yuan, Sukhwa Hong, Haopeng Zhang
Large language models (LLMs) have shown strong performance in zero-shot summarization, but often struggle to model document structure and identify salient information in long texts…
Wi-Chat: Large Language Model Powered Wi-Fi Sensing
Haopeng Zhang, Yili Ren, Haohan Yuan +2
Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse tasks. However, their potential to integrate physical model knowledge f…
DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization
Haohan Yuan, Haopeng Zhang
Most research on abstractive summarization focuses on single-domain applications, often neglecting how domain shifts between documents affect performance and the generalization abi…
A Structure-aware Generative Model for Biomedical Event Extraction
Haohan Yuan, Siu Cheung Hui, Haopeng Zhang
Biomedical Event Extraction (BEE) is a challenging task that involves modeling complex relationships between fine-grained entities in biomedical text. BEE has traditionally been fo…