779 citations
- Harvard UniversityUS8 papers
- Stanford UniversityUS8 papers
- Beijing Academy of Artificial IntelligenceCN7 papers
- Harvard University PressUS7 papers
- Monash UniversityAU7 papers
- Technical University of MunichDE6 papers
- University of Hong KongHK6 papers
- Charles Darwin UniversityAU5 papers
- The University of Texas at AustinUS5 papers
- United International UniversityBD5 papers
- University College LondonGB5 papers
- Artificial Intelligence Research InstituteES4 papers
168 papers
Frontier vision-language models have overtaken young adults at detecting AI-generated portraits -- but not their calibration
Sunwhi Kim, Sunyul Kim, Meounggun Jo +1
AI image generators now create face portraits that are hard to tell from real photographs. Vision-language models (VLMs) are increasingly proposed to flag such images. We benchmark…
The em-dash em-beds in Congress: A population-level rise in em-dash frequency in U.S. congressional press releases at the dawn of the large-language-model era, 2021-2025
Przemysław Czuma
Large language models (LLMs) can leave small stylistic traces in text written with their help. The most discussed is the em-dash (U+2014), especially the unspaced form word---word,…
IterCOMP: Reasoning-aware Adaptive Prompt Compression for Multi-hop Question Answering
JungMin Yun, YoungBin Kim
Multi-hop question answering requires complex reasoning across multiple evidence segments, which often overwhelms retrieval-augmented generation systems with lengthy and noisy cont…
Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning
Haengbok Chung, Jae Sung Lee
Class imbalance is a common problem in deep learning that severely degrades performance. In federated learning (FL), it is a critical factor contributing to non-identically distrib…
Chunking Methods on Retrieval-Augmented Generation - Effectiveness Evaluation Against Computational Cost and Limitations
Mateusz Śmigielski, Michał Rajkowski, Mateusz Zbrocki +5
Retrieval-Augmented Generation (RAG) has demonstrated significant capabilities in enhancing the performance of Large Language Models (LLMs). One of the key tasks in RAG systems is…
A Survey of Large Language Models for Perception and Measurement of Human Psychology
Yudong Li, Xiaoyi Chen, Jiawei Cai +4
Against the backdrop of the rapid advancement of Large Language Models (LLMs), their application in the field of psychology has garnered significant academic attention. A central i…