All posts by Christos Plachouras

AIM at Pretrain 2025

Work from AIM researchers was presented on June 25th at the PreTrain 2025 pre-conference presentation event. The event, hosted by the King’s College London NLP Group in the Department of Informatics at King’s College London, aimed to showcase accepted work in the ACL 2025, ICML 2025, and ICLR 2025 conferences and foster discussions.

AIM PhD student Yinghao Ma presented the following paper he coauthored with, among others, academic Emmanouil Benetos:

MuPT: A Generative Symbolic Music Pretrained Transformer, Xingwei Qu, Yuelin Bai, Yinghao Ma, Ziya Zhou, Ka Man Lo, Jiaheng Liu, Ruibin Yuan, Lejun Min, Xueling Liu, Tianyu Zhang, Xinrun Du, Shuyue Guo, Yiming Liang, Yizhi Li, Shangda Wu, Junting Zhou, Tianyu Zheng, Ziyang Ma, Fengze Han, Wei Xue, Gus Xia, Emmanouil Benetos, Xiang Yue, Chenghua Lin, Xu Tan, Stephen W. Huang, Jie Fu, Ge Zhang, accepted at ICLR 2025.


AIM at IJCNN 2025

IJCNN 2025 rome logoOn 30 June – 5 July 2025, AIM researchers will participate at the IEEE International Joint Conference on Neural Networks (IJCNN 2025), the flagship conference of the IEEE Computational Intelligence Society and the International Neural Network Society.

The following papers authored/co-authored by AIM members will be presented at IJCNN 2025:

The following presentation from an AIM PhD student will also be made at IJCNN 2025:

  • Split Fine-Tuning of BERT-based Music Models in the Edge-Cloud Continuum: An Empirical Analysis, by Bradley Aldous, Wai Fong Tam, Ahmed M. A. Sayed

See you in Rome!


AIM involvement in MIREX 2025

mirex logoMIREX (Music Information Retrieval Evaluation eXchange) is a prominent evaluation platform in the field of music information retrieval. Researchers are invited to submit novel algorithms for a variety of music-related tasks and receive standardized evaluation results, with the opportunity to present posters during the annual ISMIR conference. For more details on submission, please see the following link:

This year, AIM PhD students Yinghao Ma and Huan Zhang introduced new tasks to the platform, including Multimodal Music QA, Expressive Piano Performance Rendering, alongside traditional MIR challenges and emerging understanding/generation tasks. Specifically, we are coordinating the following tasks:

Music Reasoning QA
Task Captain: Yinghao Ma
The MIREX 2025 Music Reasoning Question Answering (QA) Task challenges participants to develop models capable of answering natural language questions that require understanding and reasoning over musical audio. This task seeks to advance the frontier of machine music intelligence by evaluating models on their ability to reason about all kinds of music information musical structure, instrument presence, melody information, vocal content, and environmental context etc., along with knowledge in music theory and music history.
Participants will build systems that answer multiple-choice questions grounded in audio inputs. The task includes questions from four curated subsets (Music, Music-Speech, Sound-Music, Sound-Music-Speech) from the MMAR benchmark, and Music-subset with image caption from the OmniBench benchmark. Each question is paired with an audio clip and 2-4 different choices.

RenCon: Expressive Piano Performance Rendering Contest
Task Captain: Huan Zhang
Expressive Performance Rendering (https://ren-con2025.vercel.app/) is a task that challenges participants to develop systems capable of rendering expressive musical performances from symbolic scores in MusicXML format. We accept system that generate symbolic (MIDI) or audio (wav) renderings, and the output shall contain human-like expressive deviation from the MusicXML score.
Similar to AI song contest, the evaluation of expressive rendering is subjective and requires human judges to assess. Thus, we have a two-phase competition structure: Phase 1 – Preliminary Round (Online) Submit performances of assigned and free-choice pieces. The submission period is open from May 30, 2025 to Aug 20, 2025. After the submission deadline, the preliminary round page will be finalized with the list of participants and their submissions, and the online evaluation will take place. Phase 2 – Live Contest at ISMIR (Daejeon, Korea) Top systems from preliminary round will be invited to render a surprise piece live at ISMIR, using their system in real time. The live contest is open to all ISMIR attendees, as well as the general public. The audience will be able to listen to the live performances and vote for their favorite system.

Audio Beat Tracking
Task Captain: Wenye Ma & Yinghao Ma
The aim of the automatic beat tracking task is to track each beat locations in a collection of sound files. Unlike the Audio Tempo Extraction task, which aim is to detect tempi for each file, the beat tracking task aims at detecting all beat locations in recordings. The algorithms will be evaluated in terms of their accuracy in predicting beat locations annotated by a group of listeners.

Audio Key Detection
Task Captain: Wenye Ma & Yinghao Ma
Audio Key Detection aims to identify the musical key (e.g., C major, A minor) of an audio recording. This involves determining both the tonic (root pitch) and the mode (major or minor) from the audio signal.