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Yinghao Li

9 papers hereh-index 7150 citations30 works total

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

author position
  • first author1
  • middle author8

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

fields
  • cs.CL6
  • cs.LG2
  • cs.SD1
same name
  • Yinghao Li — 18 papers, h 14
  • Yinghao Li — 3 papers, h 2
  • Yinghao Li — 2 papers, h 2
  • Yinghao Li — 1 paper
  • Yinghao Li — 1 paper, h 2
  • Yinghao Li — 1 paper, h 9

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
20232026
most citedMindLLM: Pre-training Lightweight Large Language Model from Scratch, Evaluations and Domain Applications

3 citations · 3 across the 9 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

Unveiling and Addressing Pseudo Forgetting in Large Language Models

Huashan Sun, Yizhe Yang, Yinghao Li +2

Although substantial efforts have been made to mitigate catastrophic forgetting in continual learning, the intrinsic mechanisms are not well understood. In this work, we demonstrat…

cs.CL2024

SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation

Bin Xu, Yiguan Lin, Yinghao Li +1

Large language models demonstrate exceptional performance in simple code generation tasks but still face challenges in tackling complex problems. These challenges may stem from ins…

cs.CL2024

Word Matters: What Influences Domain Adaptation in Summarization?

Yinghao Li, Siyu Miao, Heyan Huang +1

Domain adaptation aims to enable Large Language Models (LLMs) to generalize domain datasets unseen effectively during the training phase. However, factors such as the size of the m…

cs.CL2024

How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment

Heyan Huang, Yinghao Li, Huashan Sun +2

Recent studies have demonstrated that In-Context Learning (ICL), through the use of specific demonstrations, can align Large Language Models (LLMs) with human preferences known as…

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