LLMpeople
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Bairen Yi

Bairen Yi is a researcher at ByteDance's Seed Foundation Team. Public publication records link him to work on efficient LLM inference, KV-cache compression, and model/model-expert merging.

Researcher at ByteDance Seed Foundation Team working on efficient large language model systems and compression.1 organizations2 reports

Profile status: updated

updated 2 public sources
large language modelsmodel compressioninference optimization

Current frame

Researcher at ByteDance Seed Foundation Team working on efficient large language model systems and compression.

Extended note

Publicly available exact-source profiles identify Bairen Yi as a researcher with ByteDance's Seed Foundation Team. OpenReview lists prior study in computer science and engineering at The Hong Kong University of Science and Technology, and DBLP/OpenReview attribute publications on efficient LLM inference, KV-cache compression, and model or MoE merging.

Education

The Hong Kong University of Science and Technology Computer Science and Engineering 2015 → 2019
The Hong Kong University of Science and Technology Computer Science and Engineering 2011 → 2015

Public links

openreview OpenReview dblp DBLP

Organizations

core ByteDance Seed

Reports

Vision-Language Models Seed1.5-VL Technical Report Report Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning

Official and primary sources

dblp: Bairen Yi Official source · dblp · DBLP Bairen Yi Official source · openreview · OpenReview