Ordering Matters: Rank-Aware Selective Fusion for Blended Emotion Recognition
Junghyun Lee, Hyunseo Kim, Hanna Jang, and 1 more author
In BlEmoRe Challenge at International Conference on Automatic Face and Gesture Recognition (FGW), 2026, 2nd Place Winner in Multimodal Blended Emotion Recognition
Blended emotion recognition is challenging because emotions are often expressed as mixtures of subtle and overlapping multimodal cues rather than a single dominant signal. We propose a rank-aware multi-encoder framework that selectively combines complementary representations from diverse pre-extracted video and audio encoders.
@inproceedings{lee2026ordering,title={Ordering Matters: Rank-Aware Selective Fusion for Blended Emotion Recognition},author={Lee, Junghyun and Kim, Hyunseo and Jang, Hanna and Noh, Junhyug},booktitle={BlEmoRe Challenge at International Conference on Automatic Face and Gesture Recognition (FGW), 2026},location={2nd Place Winner in Multimodal Blended Emotion Recognition},url={https://arxiv.org/abs/2605.21417},}
ICLRW
Random Is Hard to Beat: Active Selection in Online DPO with Modern LLMs
Giyeong Oh, Junghyun Lee, Jaehyun Park, and 3 more authors
I Can’t Believe It’s Not Better (ICBINB) Workshop at International Conference on Learning Representations (ICLRW), 2026
Modern LLMs inherit strong priors from web-scale pretraining, which can limit the headroom of post-training data-selection strategies. While Active Preference Learning (APL) seeks to optimize query efficiency in online DPO, simple Random sampling proves a surprisingly formidable baseline.
@article{oh2026random,title={Random Is Hard to Beat: Active Selection in Online {DPO} with Modern {LLMs}},author={Oh, Giyeong and Lee, Junghyun and Park, Jaehyun and Yu, Youngjae and Bae, Wonho and Noh, Junhyug},journal={I Can’t Believe It’s Not Better (ICBINB) Workshop at International Conference on Learning Representations (ICLRW), 2026},url={https://arxiv.org/abs/2604.02766},}