3 citations · 6 across the 11 of their papers we have counts for
12 papers
Retrieval-Based In-Context Learning: A Domain Adaptation Framework
Yilun Zhu, Naihao Deng, Yingcong Li +2
In-context retrieval (ICR) is a retrieval-based form of in-context learning (ICL) in which demonstrations are retrieved from a source database based on similarity to the query, rat…
Multimodal Alignment Through Joint Kernel Entropic Gromov--Wasserstein Optimal Transport
Yixuan Florence Wu, Yilun Zhu, Naichen Shi
We study the problem of aligning data from multiple modalities into a shared representation space, focusing on settings where strong pretrained unimodal encoders are available but…
It Takes One to Bias Them All: Breaking Bad with One-Shot GRPO
Naihao Deng, Yilun Zhu, Naichen Shi +2
Warning: This paper contains several toxic and offensive statements. Modern large language models (LLMs) are typically aligned through large-scale post-training to ensure fair and…
Wait, am I Being Fair? Characterizing Deductive Stereotyping and Mitigating It with Fair-GCG
Naihao Deng, Yilun Zhu, Joan Nwatu +2
Warning: This paper contains several toxic and offensive statements. While reasoning generally improves fairness in recent large language models (LLMs), failures persist. In this w…
Text-to-Distribution Prediction with Quantile Tokens and Neighbor Context
Yilun Zhu, Yuan Zhuang, Nikhita Vedula +6
Many applications of LLM-based text regression require predicting a full conditional distribution rather than a single point value. We study distributional regression under empiric…
Calibrated Principal Component Regression
Yixuan Florence Wu, Yilun Zhu, Lei Cao +1
We propose a new method for statistical inference in generalized linear models. In the overparameterized regime, Principal Component Regression (PCR) reduces variance by projecting…
Domain Generalization Under Posterior Drift
Yilun Zhu, Naihao Deng, Naichen Shi +2
Domain generalization (DG) is the problem of generalizing from several distributions (or domains), for which labeled training data are available, to a new test domain for which no…
Label Noise: Ignorance Is Bliss
Yilun Zhu, Jianxin Zhang, Aditya Gangrade +1
We establish a new theoretical framework for learning under multi-class, instance-dependent label noise. This framework casts learning with label noise as a form of domain adaptati…
Characterizing the temporal dynamics of universal speech representations for generalizable deepfake detection
Yi Zhu, Saurabh Powar, Tiago H. Falk
Existing deepfake speech detection systems lack generalizability to unseen attacks (i.e., samples generated by generative algorithms not seen during training). Recent studies have…
On decoder-only architecture for speech-to-text and large language model integration
Jian Wu, Yashesh Gaur, Zhuo Chen +8
Large language models (LLMs) have achieved remarkable success in the field of natural language processing, enabling better human-computer interaction using natural language. Howeve…
Mixture Proportion Estimation Beyond Irreducibility
Yilun Zhu, Aaron Fjeldsted, Darren Holland +3
The task of mixture proportion estimation (MPE) is to estimate the weight of a component distribution in a mixture, given observations from both the component and mixture. Previous…
Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training
Eric Sun, Jinyu Li, Yuxuan Hu +8
We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users dur…