1 citations · 2 across the 4 of their papers we have counts for
5 papers
Where Does the Sound Go? Tracing Acoustic Information Loss in Audio-Conditioned LLMs
Song-ha Jo, Sehyun Lee, Soyoon Kim +2
Audio-conditioned language models often underuse acoustic cues such as prosody, emotion, and non-speech sounds, raising the question of whether ASR-supervised frontends discard thi…
Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations
Dahee Kwon, Sehyun Lee, Jaesik Choi
Deep vision models have achieved remarkable classification performance by leveraging a hierarchical architecture in which human-interpretable concepts emerge through the compositio…
Probing Network Decisions: Capturing Uncertainties and Unveiling Vulnerabilities Without Label Information
Youngju Joung, Sehyun Lee, Jaesik Choi
To improve trust and transparency, it is crucial to be able to interpret the decisions of Deep Neural classifiers (DNNs). Instance-level examinations, such as attribution technique…
Implicit Contrastive Representation Learning with Guided Stop-gradient
Byeongchan Lee, Sehyun Lee
In self-supervised representation learning, Siamese networks are a natural architecture for learning transformation-invariance by bringing representations of positive pairs closer…
Variational Neural Temporal Point Process
Deokjun Eom, Sehyun Lee, Jaesik Choi
A temporal point process is a stochastic process that predicts which type of events is likely to happen and when the event will occur given a history of a sequence of events. There…