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Wenhao Li

11 papers hereh-index 4230 citations13 works total

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

author position
  • sole author1
  • first author3
  • middle author7

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CV3
  • cs.AI2
  • cs.CC1
  • cs.CY1
same name
  • Wenhao Li — 34 papers, h 13
  • Wenhao Li — 20 papers, h 13
  • Wenhao Li — 11 papers, h 4
  • Wenhao Li — 10 papers, h 2
  • Wenhao Li — 10 papers, h 3
  • Wenhao Li — 9 papers, h 11

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
collaborators
Showing 2025Show all

4 papers · 1 filter

cs.LG2025

MOCHA: Discovering Multi-Order Dynamic Causality in Temporal Point Processes

Yunyang Cao, Juekai Lin, Wenhao Li +1

Discovering complex causal dependencies in temporal point processes (TPPs) is critical for modeling real-world event sequences. Existing methods typically rely on static or first-o…

cs.LG2025

DICE: Data Influence Cascade in Decentralized Learning

Tongtian Zhu, Wenhao Li, Can Wang +1

Decentralized learning offers a promising approach to crowdsource data consumptions and computational workloads across geographically distributed compute interconnected through pee…

cs.CY2025

Bridging Technology and Humanities: Evaluating the Impact of Large Language Models on Social Sciences Research with DeepSeek-R1

Peiran Gu, Fuhao Duan, Wenhao Li +6

In recent years, the development of Large Language Models (LLMs) has made significant breakthroughs in the field of natural language processing and has gradually been applied to th…

cs.LG2025

Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction

Yudong W. Xu, Wenhao Li, Scott Sanner +1

We present a Transformer-based framework for Constraint Satisfaction Problems (CSPs). CSPs find use in many applications and thus accelerating their solution with machine learning…

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