10 papers
Frequency-Aware Self-Supervised Music Representation Learning
Yicheng Gu, Junan Zhang, Jerry Li +2
Self-supervised learning (SSL) has emerged as an essential paradigm for music information retrieval (MIR). While current SSL models achieve state-of-the-art performance across vari…
Aliasing-Free Neural Audio Synthesis
Yicheng Gu, Junan Zhang, Chaoren Wang +3
In neural audio synthesis, neural vocoders and codecs are models that reconstruct waveforms from acoustic and latent representations, which are essential to the resulting audio qua…
Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization
Tiancheng Xing, Jerry Li, Yixuan Du +1
Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small, natural-sounding prompts. To expose th…
Optimal Inference Schedules for Masked Diffusion Models
Sitan Chen, Kevin Cong, Jerry Li
A major bottleneck of standard auto-regressive large language models is that their inference process is inherently sequential, resulting in very long and costly inference times. To…
Robust Estimation Under Heterogeneous Corruption Rates
Syomantak Chaudhuri, Jerry Li, Thomas A. Courtade
We study the problem of robust estimation under heterogeneous corruption rates, where each sample may be independently corrupted with a known but non-identical probability. This se…
Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection
Jerry Li, Evangelos Papalexakis
Large Language Models (LLMs) have demonstrated effectiveness across a wide variety of tasks involving natural language, however, a fundamental problem of hallucinations still plagu…