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Yilun Zhu

Georgetown University

11 papers hereh-index 6274 citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author6

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG2
  • stat.ML2
  • cs.SD1
  • eess.AS1
  • math.ST1
affiliations
  • Georgetown University
Homepage
same name
  • Yilun Zhu — 17 papers, h 8
  • Yilun Zhu — 1 paper, h 3
  • Yilun Zhu — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedOn decoder-only architecture for speech-to-text and large language model integration

3 citations · 6 across the 11 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

math.ST2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.