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Haochen Li

Nanyang Technological University

9 papers hereh-index 6163 citations10 works total

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

author position
  • first author5
  • middle author4

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.SE3
  • cs.CV1
  • cs.IR1
  • cs.LG1
affiliations
  • Nanyang Technological University
Homepage
same name
  • Haochen Li — 13 papers, h 7
  • Haochen Li — 12 papers, h 3
  • Haochen Li — 8 papers, h 6
  • Haochen Li — 7 papers, h 7
  • Haochen Li — 5 papers, h 2
  • Haochen Li — 3 papers, h 2

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 citedCOVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining

6 citations · 12 across the 9 of their papers we have counts for

collaborators
Showing cs.CLShow all

3 papers · 1 filter

cs.CL2026

Understand Then Memory: A Cognitive Gist-Driven RAG Framework with Global Semantic Diffusion

Pengcheng Zhou, Haochen Li, Zhiqiang Nie +4

Retrieval-Augmented Generation (RAG) effectively mitigates hallucinations in LLMs by incorporating external knowledge. However, the inherent discrete representation of text in exis…

cs.CL2024★ 2 cited

SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages

Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar +58

Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing…

cs.CL2024★ 3 cited

Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey

Haochen Li, Jonathan Leung, Zhiqi Shen

Large Language Models (LLMs) have shown prominent performance in various downstream tasks and prompt engineering plays a pivotal role in optimizing LLMs' performance. This paper, n…

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