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Xin Dong

20 papers hereh-index 6214 citations21 works total

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

author position
  • middle author5
  • last author14

Across the 19 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.CV8
  • cs.AI2
same name
  • Xin Dong — 24 papers, h 16
  • Xin Dong — 21 papers, h 23
  • Xin Dong — 21 papers, h 14
  • Xin Dong — 16 papers, h 17
  • Xin Dong — 9 papers, h 5
  • Xin Dong — 7 papers, h 6

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
20242026
most citedCRAG -- Comprehensive RAG Benchmark

8 citations · 10 across the 16 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

VisualLens: Personalization through Task-Agnostic Visual History

Wang Bill Zhu, Deqing Fu, Kai Sun +8

Existing recommendation systems either rely on user interaction logs, such as online shopping history for shopping recommendations, or focus on text signals. However, item-based hi…

cs.CL2024

Are Large Language Models a Good Replacement of Taxonomies?

Yushi Sun, Hao Xin, Kai Sun +5

Large language models (LLMs) demonstrate an impressive ability to internalize knowledge and answer natural language questions. Although previous studies validate that LLMs perform…

cs.CL2024★ 8 cited

CRAG -- Comprehensive RAG Benchmark

Xiao Yang, Kai Sun, Hao Xin +24

Retrieval-Augmented Generation (RAG) has recently emerged as a promising solution to alleviate Large Language Model (LLM)'s deficiency in lack of knowledge. Existing RAG datasets,…

cs.CV2024★ 1 cited

Lumos : Empowering Multimodal LLMs with Scene Text Recognition

Ashish Shenoy, Yichao Lu, Srihari Jayakumar +11

We introduce Lumos, the first end-to-end multimodal question-answering system with text understanding capabilities. At the core of Lumos is a Scene Text Recognition (STR) component…

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