42 citations · 57 across the 6 of their papers we have counts for
6 papers
Dynamic Tool Dependency Retrieval for Lightweight Function Calling
Bhrij Patel, Davide Belli, Amir Jalalirad +3
Function calling agents powered by Large Language Models (LLMs) select external tools to automate complex tasks. On-device agents typically use a retrieval module to select relevan…
Neural 5G Indoor Localization with IMU Supervision
Aleksandr Ermolov, Shreya Kadambi, Maximilian Arnold +8
Radio signals are well suited for user localization because they are ubiquitous, can operate in the dark and maintain privacy. Many prior works learn mappings between channel state…
Temporal Alignment for History Representation in Reinforcement Learning
Aleksandr Ermolov, Enver Sangineto, Nicu Sebe
Environments in Reinforcement Learning are usually only partially observable. To address this problem, a possible solution is to provide the agent with information about the past.…
Hyperbolic Vision Transformers: Combining Improvements in Metric Learning
Aleksandr Ermolov, Leyla Mirvakhabova, Valentin Khrulkov +2
Metric learning aims to learn a highly discriminative model encouraging the embeddings of similar classes to be close in the chosen metrics and pushed apart for dissimilar ones. Th…
Latent World Models For Intrinsically Motivated Exploration
Aleksandr Ermolov, Nicu Sebe
In this work we consider partially observable environments with sparse rewards. We present a self-supervised representation learning method for image-based observations, which arra…
Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto +1
Most of the current self-supervised representation learning (SSL) methods are based on the contrastive loss and the instance-discrimination task, where augmented versions of the sa…