{"total":35,"rows":[{"id":"2411.04996","title":"Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models","created":"2024-11-07","cited_by_count":163,"area":null},{"id":"2407.00837","title":"Towards Robust Speech Representation Learning for Thousands of Languages","created":"2024-06-30","cited_by_count":50,"area":null},{"id":"2502.06490","title":"Recent Advances in Discrete Speech Tokens: A Review","created":"2025-02-10","cited_by_count":43,"area":null},{"id":"2410.00168","title":"SSR: Alignment-Aware Modality Connector for Speech Language Models","created":"2024-09-30","cited_by_count":16,"area":null},{"id":"2408.16221","title":"SSDM: Scalable Speech Dysfluency Modeling","created":"2024-08-29","cited_by_count":13,"area":null},{"id":"2512.19687","title":"Pushing the Frontier of Audiovisual Perception with Large-Scale Multimodal Correspondence Learning","created":"2025-12-22","cited_by_count":13,"area":null},{"id":"2505.02707","title":"Voila: Voice-Language Foundation Models for Real-Time Autonomous Interaction and Voice Role-Play","created":"2025-05-05","cited_by_count":10,"area":null},{"id":"2410.24177","title":"DC-Spin: A Speaker-invariant Speech Tokenizer for Spoken Language Models","created":"2024-10-31","cited_by_count":9,"area":null},{"id":"2512.20308","title":"SpidR: Learning Fast and Stable Linguistic Units for Spoken Language Models Without Supervision","created":"2025-12-23","cited_by_count":8,"area":null},{"id":"2311.09117","title":"R-Spin: Efficient Speaker and Noise-invariant Representation Learning with Acoustic Pieces","created":"2023-11-15","cited_by_count":7,"area":null},{"id":"2506.18843","title":"USAD: Universal Speech and Audio Representation via Distillation","created":"2025-06-23","cited_by_count":7,"area":null},{"id":"2401.08833","title":"Revisiting Self-supervised Learning of Speech Representation from a Mutual Information Perspective","created":"2024-01-16","cited_by_count":5,"area":null},{"id":"2402.13723","title":"The Effect of Batch Size on Contrastive Self-Supervised Speech Representation Learning","created":"2024-02-21","cited_by_count":5,"area":null},{"id":"2410.15017","title":"DM-Codec: Distilling Multimodal Representations for Speech Tokenization","created":"2024-10-19","cited_by_count":5,"area":null},{"id":"2503.00733","title":"UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation","created":"2025-03-02","cited_by_count":5,"area":null},{"id":"2504.18539","title":"Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation","created":"2025-01-23","cited_by_count":5,"area":null},{"id":"2505.21138","title":"Leveraging LLM and Self-Supervised Training Models for Speech Recognition in Chinese Dialects: A Comparative Analysis","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2511.11124","title":"AV-Dialog: Spoken Dialogue Models with Audio-Visual Input","created":"2025-11-14","cited_by_count":5,"area":null},{"id":"2406.07696","title":"Sustainable self-supervised learning for speech representations","created":"2024-06-11","cited_by_count":4,"area":null},{"id":"2410.13179","title":"EH-MAM: Easy-to-Hard Masked Acoustic Modeling for Self-Supervised Speech Representation Learning","created":"2024-10-17","cited_by_count":4,"area":null},{"id":"2509.22220","title":"StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs","created":"2025-09-26","cited_by_count":4,"area":null},{"id":"2505.11904","title":"K*-Means: A Parameter-free Clustering Algorithm","created":"2025-05-17","cited_by_count":3,"area":null},{"id":"2511.16639","title":"Codec2Vec: Self-Supervised Speech Representation Learning Using Neural Speech Codecs","created":"2025-11-20","cited_by_count":3,"area":null},{"id":"2312.11142","title":"Efficiency-oriented approaches for self-supervised speech representation learning","created":"2023-12-18","cited_by_count":1,"area":null},{"id":"2409.19448","title":"Advanced Clustering Techniques for Speech Signal Enhancement: A Review and Metanalysis of Fuzzy C-Means, K-Means, and Kernel Fuzzy C-Means Methods","created":"2024-09-28","cited_by_count":1,"area":null},{"id":"2506.21712","title":"Identifying Speaker Information in Feed-Forward Layers of Self-Supervised Speech Transformers","created":"2025-06-26","cited_by_count":1,"area":null},{"id":"2509.08116","title":"Domain Knowledge is Power: Leveraging Physiological Priors for Self Supervised Representation Learning in Electrocardiography","created":"2025-09-09","cited_by_count":1,"area":null},{"id":"2512.19612","title":"MauBERT: Universal Phonetic Inductive Biases for Few-Shot Acoustic Units Discovery","created":"2025-12-22","cited_by_count":1,"area":null},{"id":"2512.21204","title":"SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation","created":"2025-12-24","cited_by_count":1,"area":null},{"id":"2601.00100","title":"Learning Speech Representations with Variational Predictive Coding","created":"2025-12-31","cited_by_count":0,"area":null},{"id":"2603.18676","title":"MANAR: Memory-augmented Attention with Navigational Abstract Conceptual Representation","created":"2026-03-19","cited_by_count":0,"area":null},{"id":"2608.19084","title":"Cluster Assignments in Soft Targets Shape Speech Representations: Evidence from S-JEPA","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2609.26748","title":"Automatic depth-based local center clustering via $\\beta$-integrated local depth and adaptive grouping","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2610.16273","title":"Deep Speech Representations Track Word Timing along a Low-Dimensional Circular Trajectory","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.19722","title":"ONCship: A Large-Scale Underwater Acoustic Corpus for Ship Recognition","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}