40 citations · 47 across the 16 of their papers we have counts for
5 papers · 1 filter
HFI: A unified framework for training-free detection and implicit watermarking of latent diffusion model generated images
Sungik Choi, Hankook Lee, Jaehoon Lee +3
Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-generated image detection methods assu…
EXAONE 3.5: Series of Large Language Models for Real-world Use Cases
Soyoung An, Kyunghoon Bae, Eunbi Choi +29
This technical report introduces the EXAONE 3.5 instruction-tuned language models, developed and released by LG AI Research. The EXAONE 3.5 language models are offered in three con…
EXAONE 3.0 7.8B Instruction Tuned Language Model
Soyoung An, Kyunghoon Bae, Eunbi Choi +34
We introduce EXAONE 3.0 instruction-tuned language model, the first open model in the family of Large Language Models (LLMs) developed by LG AI Research. Among different model size…
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning
Janghoon Han, Changho Lee, Joongbo Shin +3
Instruction tuning has emerged as a powerful technique, significantly boosting zero-shot performance on unseen tasks. While recent work has explored cross-lingual generalization by…
Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific Tasks
Changho Lee, Janghoon Han, Seonghyeon Ye +3
Instruction tuning has been proven effective in enhancing zero-shot generalization across various tasks and in improving the performance of specific tasks. For task-specific improv…