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Qi Dai

22 papers hereh-index 7156 citations29 works total

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

author position
  • middle author20

Across the 20 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.CL5
  • cs.AI4
  • cs.IR1
  • cs.SE1
same name
  • Qi Dai — 26 papers, h 30
  • Qi Dai — 9 papers, h 4
  • Qi Dai — 7 papers, h 4
  • Qi Dai — 7 papers, h 6
  • Qi Dai — 4 papers, h 5
  • Qi Dai — 3 papers, h 1

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 citedLLM2CLIP: Powerful Language Model Unlocks Richer Cross-Modality Representation

2 citations · 3 across the 19 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

AesCode: Aesthetic Code Generation with Decoupled Cross-Modal Rewards

Xin Gao, Yifan Yang, Xin Li +13

Generating information-rich visual artifacts such as slides, posters, and dashboards as code is appealing because the outputs are structured, editable, and verifiable. Yet code mod…

cs.AI2026

ReDeck: Step-Level Render-Grounded Refinement for Document-to-Slide Generation

Muzhao Tian, Zezi Zeng, Yifan Yang +14

Document-to-slide generation is challenging because slides are dense editable artifacts that require both faithful content selection and precise spatial layout. Recent slide agents…

cs.AI2026★ 1 cited

SkillOpt: Executive Strategy for Self-Evolving Agent Skills

Yifan Yang, Ziyang Gong, Weiquan Huang +12

Agent skills today are hand-crafted, generated one-shot, or evolved through loosely controlled self-revision, none of which behaves like a deep-learning optimizer for the skill, an…

cs.AI2026

From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills

Zisu Huang, Jingwen Xu, Yifan Yang +13

Language agents increasingly improve by reusing \emph{skills} -- structured procedural artifacts distilled from past experience. In particular, \emph{domain-level} and \emph{model-…

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