5 papers
EmoMed: An Emotionally-Aware Agent for Multimodal Medical Support with Real-Time Information Retrieval
Ivan Nasonov, Nikita Glazkov, Ivan Makovetskiy +4
We present EmoMed - a multimodal medical consultation agent that adapts its responses based on users' emotional states while maintaining clinical accuracy. The system processes tex…
Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation
Nikita Severin, Danil Kartushov, Vladislav Urzhumov +8
Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in capturing rich user semantics beyond interaction patterns.…
Beyond Isolated Clients: Integrating Graph-Based Embeddings into Event Sequence Models
Harry Proshian, Nikita Severin, Sergey Nikolenko +5
Large-scale digital platforms generate billions of timestamped user-item interactions (events) that are crucial for predicting user attributes in, e.g., fraud prevention and recomm…
Multi-Track Multimodal Learning on iMiGUE: Micro-Gesture and Emotion Recognition
Arman Martirosyan, Shahane Tigranyan, Maria Razzhivina +5
Micro-gesture recognition and behavior-based emotion prediction are both highly challenging tasks that require modeling subtle, fine-grained human behaviors, primarily leveraging v…
ATGen: A Framework for Active Text Generation
Akim Tsvigun, Daniil Vasilev, Ivan Tsvigun +12
Active learning (AL) has demonstrated remarkable potential in reducing the annotation effort required for training machine learning models. However, despite the surging popularity…