1 citations · 1 across the 8 of their papers we have counts for
8 papers
Smell with Genji: Rediscovering Human Perception through an Olfactory Game with AI
Awu Chen, Vera Yu Wu, Yunge Wen +7
Olfaction plays an important role in human perception, yet its subjective and ephemeral nature makes it difficult to articulate, compare, and share across individuals. Traditional…
A Vision for Multisensory Intelligence: Sensing, Science, and Synergy
Paul Pu Liang
Our experience of the world is multisensory, spanning a synthesis of language, sight, sound, touch, taste, and smell. Yet, artificial intelligence has primarily advanced in digital…
When One Modality Sabotages the Others: A Diagnostic Lens on Multimodal Reasoning
Chenyu Zhang, Minsol Kim, Shohreh Ghorbani +4
Despite rapid growth in multimodal large language models (MLLMs), their reasoning traces remain opaque: it is often unclear which modality drives a prediction, how conflicts are re…
Machine Olfaction and Embedded AI Are Shaping the New Global Sensing Industry
Andreas Mershin, Nikolas Stefanou, Adan Rotteveel +7
Machine olfaction is rapidly emerging as a transformative capability, with applications spanning non-invasive medical diagnostics, industrial monitoring, agriculture, and security…
EQPO: Equitable Group Relative Policy Optimization for Clinical Reasoning
Shiqi Dai, Wei Dai, Jiaee Cheong +1
Medical AI systems demonstrated impressive diagnostic performance, yet they routinely show uneven accuracy across demographic groups, disadvantaging underrepresented populations. A…
Human Behavior Atlas: Benchmarking Unified Psychological and Social Behavior Understanding
Keane Ong, Wei Dai, Carol Li +8
Using intelligent systems to perceive psychological and social behaviors, that is, the underlying affective, cognitive, and pathological states that are manifested through observab…
FairSSL: Fair Multimodal Self-Supervised Learning
Jiaee Cheong, Abtin Mogharabin, Paul Liang +2
Prevalent multimodal self-supervised learning (SSL) methods rely on the redundancy assumption: that different views share substantial task-relevant information. We argue that this…
Balancing Multimodal Training Through Game-Theoretic Regularization
Konstantinos Kontras, Thomas Strypsteen, Christos Chatzichristos +3
Multimodal learning holds promise for richer information extraction by capturing dependencies across data sources. Yet, current training methods often underperform due to modality…