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Ling Chen

14 papers hereh-index 8198 citations15 works total

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

author position
  • middle author10
  • last author3

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CL5
  • cs.CV5
  • cs.RO2
  • cs.AI1
  • cs.IR1
same name
  • Ling Chen — 27 papers, h 35
  • Ling Chen — 9 papers, h 5
  • Ling Chen — 9 papers, h 4
  • Ling Chen — 9 papers, h 1
  • Ling Chen — 8 papers, h 5
  • Ling Chen — 7 papers, h 30

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
20232025
most citedRetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering

1 citations · 1 across the 13 of their papers we have counts for

collaborators
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025

UniVid: The Open-Source Unified Video Model

Jiabin Luo, Junhui Lin, Zeyu Zhang +4

Unified video modeling that combines generation and understanding capabilities is increasingly important but faces two key challenges: maintaining semantic faithfulness during flow…

cs.CV2025

VaseVQA: Multimodal Agent and Benchmark for Ancient Greek Pottery

Jinchao Ge, Tengfei Cheng, Biao Wu +7

Understanding cultural heritage artifacts such as ancient Greek pottery requires expert-level reasoning that remains challenging for current MLLMs due to limited domain-specific da…

cs.CV2025

PresentAgent: Multimodal Agent for Presentation Video Generation

Jingwei Shi, Zeyu Zhang, Biao Wu +4

We present PresentAgent, a multimodal agent that transforms long-form documents into narrated presentation videos. While existing approaches are limited to generating static slides…

cs.CV2025

Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing

Baode Wang, Biao Wu, Weizhen Li +8

Automated parsing of scanned documents into richly structured, machine-readable formats remains a critical bottleneck in Document AI, as traditional multi-stage pipelines suffer fr…

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