3 citations · 12 across the 14 of their papers we have counts for
15 papers
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop
Sayantan Adak, Rima Hazra, Koyel Mukherjee +2
Large language models can produce fluent tu- toring dialogue, but whether they actually help students learn remains unclear. We present a process-centered synthesis of LLM tutoring…
Towards Child-Inclusive Clinical Video Understanding for Autism Spectrum Disorder
Aditya Kommineni, Digbalay Bose, Tiantian Feng +6
Clinical videos in the context of Autism Spectrum Disorder are often long-form interactions between children and caregivers/clinical professionals, encompassing complex verbal and…
Can Text-to-image Model Assist Multi-modal Learning for Visual Recognition with Visual Modality Missing?
Tiantian Feng, Daniel Yang, Digbalay Bose +1
Multi-modal learning has emerged as an increasingly promising avenue in vision recognition, driving innovations across diverse domains ranging from media and education to healthcar…
Does Video Summarization Require Videos? Quantifying the Effectiveness of Language in Video Summarization
Yoonsoo Nam, Adam Lehavi, Daniel Yang +3
Video summarization remains a huge challenge in computer vision due to the size of the input videos to be summarized. We propose an efficient, language-only video summarizer that a…
MM-AU:Towards Multimodal Understanding of Advertisement Videos
Digbalay Bose, Rajat Hebbar, Tiantian Feng +3
Advertisement videos (ads) play an integral part in the domain of Internet e-commerce as they amplify the reach of particular products to a broad audience or can serve as a medium…
FedMultimodal: A Benchmark For Multimodal Federated Learning
Tiantian Feng, Digbalay Bose, Tuo Zhang +6
Over the past few years, Federated Learning (FL) has become an emerging machine learning technique to tackle data privacy challenges through collaborative training. In the Federate…
Unlocking Foundation Models for Privacy-Enhancing Speech Understanding: An Early Study on Low Resource Speech Training Leveraging Label-guided Synthetic Speech Content
Tiantian Feng, Digbalay Bose, Xuan Shi +1
Automatic Speech Understanding (ASU) leverages the power of deep learning models for accurate interpretation of human speech, leading to a wide range of speech applications that en…
Signal Processing Grand Challenge 2023 -- e-Prevention: Sleep Behavior as an Indicator of Relapses in Psychotic Patients
Kleanthis Avramidis, Kranti Adsul, Digbalay Bose +1
This paper presents the approach and results of USC SAIL's submission to the Signal Processing Grand Challenge 2023 - e-Prevention (Task 2), on detecting relapses in psychotic pati…
Contextually-rich human affect perception using multimodal scene information
Digbalay Bose, Rajat Hebbar, Krishna Somandepalli +1
The process of human affect understanding involves the ability to infer person specific emotional states from various sources including images, speech, and language. Affect percept…
A dataset for Audio-Visual Sound Event Detection in Movies
Rajat Hebbar, Digbalay Bose, Krishna Somandepalli +2
Audio event detection is a widely studied audio processing task, with applications ranging from self-driving cars to healthcare. In-the-wild datasets such as Audioset have propelle…
Multimodal Estimation of Change Points of Physiological Arousal in Drivers
Kleanthis Avramidis, Tiantian Feng, Digbalay Bose +1
Detecting unsafe driving states, such as stress, drowsiness, and fatigue, is an important component of ensuring driving safety and an essential prerequisite for automatic intervent…
MovieCLIP: Visual Scene Recognition in Movies
Digbalay Bose, Rajat Hebbar, Krishna Somandepalli +5
Longform media such as movies have complex narrative structures, with events spanning a rich variety of ambient visual scenes. Domain specific challenges associated with visual sce…
Understanding of Emotion Perception from Art
Digbalay Bose, Krishna Somandepalli, Souvik Kundu +3
Computational modeling of the emotions evoked by art in humans is a challenging problem because of the subjective and nuanced nature of art and affective signals. In this paper, we…
Cross Domain Emotion Recognition using Few Shot Knowledge Transfer
Justin Olah, Sabyasachee Baruah, Digbalay Bose +1
Emotion recognition from text is a challenging task due to diverse emotion taxonomies, lack of reliable labeled data in different domains, and highly subjective annotation standard…
Clustering using Vector Membership: An Extension of the Fuzzy C-Means Algorithm
Srinjoy Ganguly, Digbalay Bose, Amit Konar
Clustering is an important facet of explorative data mining and finds extensive use in several fields. In this paper, we propose an extension of the classical Fuzzy C-Means cluster…