5 citations · 6 across the 7 of their papers we have counts for
8 papers
Training a Compact, Strong, and Realistic Text-to-Speech Model
Runyuan Cai, Yu Lin, Yiming Wang +1
Text-to-speech (TTS) systems are conventionally optimized for intelligibility and speaker similarity. However, neither objective captures the prosodic detail that distinguishes hum…
Data-Efficient On-Policy Distillation for Automatic Speech Recognition
Yu Lin, Yiming Wang, Runyuan Cai +1
Building competitive automatic speech recognition (ASR) models usually requires large-scale au- dio supervision, which makes reproduction and specialization expensive. We study Ark…
ROAR: Retrieval Opportunity-Aware Refinement for Zero-Shot Time Series Forecasting
Jinjin Chi, Lei Feng, Lulu Zhang +7
Retrieval augmentation provides time series forecasters with historical continuations, yet even candidates that outperform the base forecast may fail to improve the final predictio…
Zero-Shot Temporal Action Localization Through Textual Guidance
Benedetta Liberatori, Alessandro Conti, Lorenzo Vaquero +3
Zero-shot temporal action localization (ZS-TAL) consists of classifying and localizing actions in untrimmed videos, where action classes are unseen at training time. Existing work…
Tiny-Engram: Trigger-Indexed Concept Tables for Generative Vision
Runyuan Cai, Yiming Wang, Yu Lin +1
Current personalization methods for generative vision models typically encode new concepts through continuous adapters or weight updates, yet provide limited control over whether a…
Unifying Speech Recognition, Synthesis and Conversion with Autoregressive Transformers
Runyuan Cai, Yu Lin, Yiming Wang +2
Traditional speech systems typically rely on separate, task-specific models for text-to-speech (TTS), automatic speech recognition (ASR), and voice conversion (VC), resulting in fr…
PrivateLoRA For Efficient Privacy Preserving LLM
Yiming Wang, Yu Lin, Xiaodong Zeng +1
End users face a choice between privacy and efficiency in current Large Language Model (LLM) service paradigms. In cloud-based paradigms, users are forced to compromise data locali…
MultiLoRA: Democratizing LoRA for Better Multi-Task Learning
Yiming Wang, Yu Lin, Xiaodong Zeng +1
LoRA achieves remarkable resource efficiency and comparable performance when adapting LLMs for specific tasks. Since ChatGPT demonstrated superior performance on various tasks, the…