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Dongfang Liu

42 papers hereh-index 242.2k citations37 works total

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

author position
  • first author2
  • middle author17
  • last author22

Across the 41 of 42 papers where every author was matched, so the position is known.

fields
  • cs.CV31
  • cs.CL4
  • cs.LG4
  • cs.CR1
  • cs.RO1
  • physics.comp-ph1
same name
  • Dongfang Liu — 10 papers, h 10
  • Dongfang Liu — 5 papers, h 10
  • Dongfang Liu — 4 papers, h 4
  • Dongfang Liu — 2 papers, h 0
  • Dongfang Liu — 1 paper
  • Dongfang Liu — 1 paper

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
20202026
most citedGL-RG: Global-Local Representation Granularity for Video Captioning

55 citations · 264 across the 40 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

Xiang Zhang, Varchas Gopalaswamy, Rahman Ejaz +2

Inertial confinement fusion (ICF) is a leading pathway toward clean energy, but each shot at the National Ignition Facility costs on the order of one million dollars, making accura…

cs.LG2024★ 4 cited

Visual Agents as Fast and Slow Thinkers

Guangyan Sun, Mingyu Jin, Zhenting Wang +7

Achieving human-level intelligence requires refining cognitive distinctions between System 1 and System 2 thinking. While contemporary AI, driven by large language models, demonstr…

cs.LG2024

Inertial Confinement Fusion Forecasting via Large Language Models

Mingkai Chen, Taowen Wang, Shihui Cao +10

Controlled fusion energy is deemed pivotal for the advancement of human civilization. In this study, we introduce LPI-LLM, a novel integration of Large Language Models (…

cs.LG2022

Deep Partial Multiplex Network Embedding

Qifan Wang, Yi Fang, Anirudh Ravula +5

Network embedding is an effective technique to learn the low-dimensional representations of nodes in networks. Real-world networks are usually with multiplex or having multi-view r…

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