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E. Wang

4 papers hereh-index 226 citations5 works total

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

author position
  • first author4

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

fields
  • cs.CV3
  • cs.AI1
same name
  • E. Wang — 108 papers, h 13
  • E. Wang — 102 papers, h 27
  • E. Wang — 33 papers, h 20
  • E. Wang — 28 papers, h 79
  • E. Wang — 23 papers, h 20
  • E. Wang — 15 papers

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
20222026
most citedRoViST:Learning Robust Metrics for Visual Storytelling

1 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2026

MMCOMET: A Large-Scale Multimodal Commonsense Knowledge Graph for Contextual Reasoning

Eileen Wang, Hiba Arnaout, Dhita Pratama +6

We present MMCOMET, the first multimodal commonsense knowledge graph (MMKG) that integrates physical, social, and eventive knowledge. MMCOMET extends the ATOMIC2020 knowledge graph…

cs.CV2024★ 1 cited

GEM-VPC: A dual Graph-Enhanced Multimodal integration for Video Paragraph Captioning

Eileen Wang, Caren Han, Josiah Poon

Video Paragraph Captioning (VPC) aims to generate paragraph captions that summarises key events within a video. Despite recent advancements, challenges persist, notably in effectiv…

cs.CV2024

SCO-VIST: Social Interaction Commonsense Knowledge-based Visual Storytelling

Eileen Wang, Soyeon Caren Han, Josiah Poon

Visual storytelling aims to automatically generate a coherent story based on a given image sequence. Unlike tasks like image captioning, visual stories should contain factual descr…

cs.CV2022★ 1 cited

RoViST:Learning Robust Metrics for Visual Storytelling

Eileen Wang, Caren Han, Josiah Poon

Visual storytelling (VST) is the task of generating a story paragraph that describes a given image sequence. Most existing storytelling approaches have evaluated their models using…

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