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researcher

Yu Bai

4 papers hereh-index 345 citations7 works total

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

author position
  • first author2
  • middle author1
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CL1
  • cs.CV1
  • cs.IR1
same name
  • Yu Bai — 28 papers, h 23
  • Yu Bai — 22 papers
  • Yu Bai — 19 papers, h 18
  • Yu Bai — 19 papers, h 15
  • Yu Bai — 13 papers, h 9
  • Yu Bai — 8 papers, h 35

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 citedAn Empirical Study of NetOps Capability of Pre-Trained Large Language Models

7 citations · 7 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

SEDiT: Mask-Free Video Subtitle Erasure via One-step Diffusion Transformer

Zheng Hui, Yunlong Bai

Recent breakthroughs in video diffusion models have significantly accelerated the development of video editing techniques. However, existing methods often rely on inpainting video…

cs.AI2025

DMA: Online RAG Alignment with Human Feedback

Yu Bai, Yukai Miao, Dawei Wang +9

Retrieval-augmented generation (RAG) systems often rely on static retrieval, limiting adaptation to evolving intent and content drift. We introduce Dynamic Memory Alignment (DMA),…

cs.IR2024

Pistis-RAG: Enhancing Retrieval-Augmented Generation with Human Feedback

Yu Bai, Yukai Miao, Li Chen +6

RAG systems face limitations when semantic relevance alone does not guarantee improved generation quality. This issue becomes particularly evident due to the sensitivity of large l…

cs.CL2023★ 7 cited

An Empirical Study of NetOps Capability of Pre-Trained Large Language Models

Yukai Miao, Yu Bai, Li Chen +10

Nowadays, the versatile capabilities of Pre-trained Large Language Models (LLMs) have attracted much attention from the industry. However, some vertical domains are more interested…

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