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Richang Hong

7 papers hereh-index 349 citations17 works total

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

author position
  • middle author3
  • last author4

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.MM2
  • cs.CL1
  • cs.HC1
  • cs.LG1
same name
  • Richang Hong — 55 papers, h 72
  • Richang Hong — 19 papers, h 24
  • Richang Hong — 18 papers, h 4
  • Richang Hong — 17 papers, h 11
  • Richang Hong — 12 papers, h 7
  • Richang Hong — 11 papers, h 5

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 citedTowards Multimodal Emotional Support Conversation Systems

5 citations · 5 across the 6 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.HC2024

InterMind: Doctor-Patient-Family Interactive Depression Assessment Empowered by Large Language Models

Zhiyuan Zhou, Jilong Liu, Sanwang Wang +3

Depression poses significant challenges to patients and healthcare organizations, necessitating efficient assessment methods. Existing paradigms typically focus on a patient-doctor…

cs.CV2024

SDI-Net: Toward Sufficient Dual-View Interaction for Low-light Stereo Image Enhancement

Linlin Hu, Ao Sun, Shijie Hao +2

Currently, most low-light image enhancement methods only consider information from a single view, neglecting the correlation between cross-view information. Therefore, the enhancem…

cs.MM2024★ 5 cited

Towards Multimodal Emotional Support Conversation Systems

Yuqi Chu, Lizi Liao, Zhiyuan Zhou +2

The integration of conversational artificial intelligence (AI) into mental health care promises a new horizon for therapist-client interactions, aiming to closely emulate the depth…

cs.CV2024

Controllable Relation Disentanglement for Few-Shot Class-Incremental Learning

Yuan Zhou, Richang Hong, Yanrong Guo +3

In this paper, we propose to tackle Few-Shot Class-Incremental Learning (FSCIL) from a new perspective, i.e., relation disentanglement, which means enhancing FSCIL via disentanglin…

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