activity
20212025
most citedEnhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive Learning

7 citations · 13 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2025

SCOPE: Language Models as One-Time Teacher for Hierarchical Planning in Text Environments

Haoye Lu, Pavan Seshadri, Kaheer Suleman

Long-term planning in complex, text-based environments presents significant challenges due to open-ended action spaces, ambiguous observations, and sparse feedback. Recent research…

cs.SD2025

Uncertainty Estimation in the Real World: A Study on Music Emotion Recognition

Karn N. Watcharasupat, Yiwei Ding, T. Aleksandra Ma +2

Any data annotation for subjective tasks shows potential variations between individuals. This is particularly true for annotations of emotional responses to musical stimuli. While…

cs.IR2024★ 7 cited

Enhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive Learning

Pavan Seshadri, Shahrzad Shashaani, Peter Knees

Modern music streaming services are heavily based on recommendation engines to serve content to users. Sequential recommendation -- continuously providing new items within a single…

eess.AS2024★ 4 cited

Understanding Pedestrian Movement Using Urban Sensing Technologies: The Promise of Audio-based Sensors

Chaeyeon Han, Pavan Seshadri, Yiwei Ding +5

While various sensors have been deployed to monitor vehicular flows, sensing pedestrian movement is still nascent. Yet walking is a significant mode of travel in many cities, espec…

cs.IR2023★ 1 cited

Leveraging Negative Signals with Self-Attention for Sequential Music Recommendation

Pavan Seshadri, Peter Knees

Music streaming services heavily rely on their recommendation engines to continuously provide content to their consumers. Sequential recommendation consequently has seen considerab…

eess.AS2023

ASPED: An Audio Dataset for Detecting Pedestrians

Pavan Seshadri, Chaeyeon Han, Bon-Woo Koo +3

We introduce the new audio analysis task of pedestrian detection and present a new large-scale dataset for this task. While the preliminary results prove the viability of using aud…

eess.AS2021★ 1 cited

AVASpeech-SMAD: A Strongly Labelled Speech and Music Activity Detection Dataset with Label Co-Occurrence

Yun-Ning Hung, Karn N. Watcharasupat, Chih-Wei Wu +4

We propose a dataset, AVASpeech-SMAD, to assist speech and music activity detection research. With frame-level music labels, the proposed dataset extends the existing AVASpeech dat…

cs.SD2021

Improving Music Performance Assessment with Contrastive Learning

Pavan Seshadri, Alexander Lerch

Several automatic approaches for objective music performance assessment (MPA) have been proposed in the past, however, existing systems are not yet capable of reliably predicting r…