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20242026
most citedNatureLM-audio: an Audio-Language Foundation Model for Bioacoustics

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

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7 papers · 1 filter

cs.SD2026

BEANS-Next and ROOTS: Broadening Audio-Language Capabilities for Bioacoustics

Christos Plachouras, David Robinson, Marius Miron +17

Bioacoustics and ethology encompass a wide range of audio understanding tasks, many of which stand to benefit from recent advances in large audio-language models. However, progress…

cs.LG2026

Beyond task performance: Decoding bioacoustic embeddings with speech features

Ines Nolasco, Jules Cauzinille, Marius Miron +8

Pretrained audio embeddings are standard in bioacoustics, yet little is known about which acoustic features these models encode, nor which are useful for a given task. This hinders…

cs.SD2026

Multi-layer attentive probing improves transfer of audio representations for bioacoustics

Marius Miron, David Robinson, Masato Hagiwara +15

Probing heads map the representations learned from audio by a machine learning model to downstream task labels and are a key component in evaluating representation learning. Most b…

cs.LG2026

Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification

Eklavya Sarkar, Marius Miron, David Robinson +6

Animals hear and vocalize across frequency ranges that differ substantially from humans, often extending into the ultrasonic domain. Yet most computational bioacoustics systems rel…

cs.CL2026

BAGEL: Benchmarking Animal Knowledge Expertise in Language Models

Jiacheng Shen, Masato Hagiwara, Milad Alizadeh +9

Large language models have shown strong performance on broad-domain knowledge and reasoning benchmarks, but it remains unclear how well language models handle specialized animal-re…

cs.SD2026

Audio-to-Image Bird Species Retrieval without Audio-Image Pairs via Text Distillation

Ilyass Moummad, Marius Miron, Lukas Rauch +5

Audio-to-image retrieval offers an interpretable alternative to audio-only classification for bioacoustic species recognition, but learning aligned audio-image representations is c…

cs.IR2026

Compact Hypercube Embeddings for Fast Text-based Wildlife Observation Retrieval

Ilyass Moummad, Marius Miron, David Robinson +7

Large-scale biodiversity monitoring platforms increasingly rely on multimodal wildlife observations. While recent foundation models enable rich semantic representations across visi…