◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Rui Li

Stanford University

4 papers hereh-index 4114 citations4 works total

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1
  • cs.CV1
affiliations
  • Stanford University
Homepage
same name
  • Rui Li — 29 papers, h 76
  • Rui Li — 17 papers, h 8
  • Rui Li — 14 papers, h 9
  • Rui Li — 13 papers, h 8
  • Rui Li — 12 papers, h 6
  • Rui Li — 12 papers, h 15

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
20232025
most citedTELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision

7 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

Temporal Preference Optimization for Long-Form Video Understanding

Rui Li, Xiaohan Wang, Yuhui Zhang +3

Despite significant advancements in video large multimodal models (video-LMMs), achieving effective temporal grounding in long-form videos remains a challenge for existing models.…

cs.CL2024★ 7 cited

TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision

Yunyi Zhang, Ruozhen Yang, Xueqiang Xu +4

Hierarchical text classification aims to categorize each document into a set of classes in a label taxonomy, which is a fundamental web text mining task with broad applications suc…

cs.LG2024★ 1 cited

Similarity-based Neighbor Selection for Graph LLMs

Rui Li, Jiwei Li, Jiawei Han +1

Text-attributed graphs (TAGs) present unique challenges for direct processing by Language Learning Models (LLMs), yet their extensive commonsense knowledge and robust reasoning cap…

cs.LG2023

Are Human-generated Demonstrations Necessary for In-context Learning?

Rui Li, Guoyin Wang, Jiwei Li

Despite the promising few-shot ability of large language models (LLMs), the standard paradigm of In-context Learning (ICL) suffers the disadvantages of susceptibility to selected d…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.