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Ruiming Tang

4 papers hereh-index 16839 citations34 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CL2
  • cs.AI1
  • cs.IR1
same name
  • Ruiming Tang — 40 papers, h 45
  • Ruiming Tang — 38 papers
  • Ruiming Tang — 3 papers
  • Ruiming Tang — 2 papers
  • Ruiming Tang — 2 papers
  • Ruiming Tang — 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

most citedPerformance Law of Large Language Models

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

collaborators

4 papers

cs.AI2025

Boost, Disentangle, and Customize: A Robust System2-to-System1 Pipeline for Code Generation

Kounianhua Du, Hanjing Wang, Jianxing Liu +7

Large language models (LLMs) have demonstrated remarkable capabilities in various domains, particularly in system 1 tasks, yet the intricacies of their problem-solving mechanisms i…

cs.IR2025

FuXi-α: Scaling Recommendation Model with Feature Interaction Enhanced Transformer

Yufei Ye, Wei Guo, Jin Yao Chin +8

Inspired by scaling laws and large language models, research on large-scale recommendation models has gained significant attention. Recent advancements have shown that expanding se…

cs.CL2025★ 2 cited

A Survey on Multi-Turn Interaction Capabilities of Large Language Models

Chen Zhang, Xinyi Dai, Yaxiong Wu +4

Multi-turn interaction in the dialogue system research refers to a system's ability to maintain context across multiple dialogue turns, enabling it to generate coherent and context…

cs.CL2024★ 2 cited

Performance Law of Large Language Models

Chuhan Wu, Ruiming Tang

Guided by the belief of the scaling law, large language models (LLMs) have achieved impressive performance in recent years. However, scaling law only gives a qualitative estimation…

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