activity
20242026
most citedReinforcement World Model Learning for LLM-based Agents

1 citations · 1 across the 7 of their papers we have counts for

collaborators
Showing cs.SDShow all

5 papers · 1 filter

cs.SD2026

RIME: Enabling Large-Scale Agentic Music Post-Production

Noah Schaffer, Nikhil Singh

Almost every piece of recorded music you have ever heard was modified before it reached you; commercial releases rarely spring fully-formed from the mind of a musician. Despite the…

cs.SD2026

Discovering and Steering Interpretable Concepts in Large Generative Music Models

Nikhil Singh, Manuel Cherep, Pattie Maes

The fidelity with which neural networks can now generate content such as music presents a scientific opportunity: these systems appear to have learned implicit theories of such con…

cs.SD2025

Contrastive Learning from Synthetic Audio Doppelgängers

Manuel Cherep, Nikhil Singh

Learning robust audio representations currently demands extensive datasets of real-world sound recordings. By applying artificial transformations to these recordings, models can le…

cs.SD2024

Looking Similar, Sounding Different: Leveraging Counterfactual Cross-Modal Pairs for Audiovisual Representation Learning

Nikhil Singh, Chih-Wei Wu, Iroro Orife +1

Audiovisual representation learning typically relies on the correspondence between sight and sound. However, there are often multiple audio tracks that can correspond with a visual…

cs.SD2024

Creative Text-to-Audio Generation via Synthesizer Programming

Manuel Cherep, Nikhil Singh, Jessica Shand

Neural audio synthesis methods now allow specifying ideas in natural language. However, these methods produce results that cannot be easily tweaked, as they are based on large late…