◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Fang Wu

4 papers hereh-index 585 citations7 works total

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

author position
  • first author2
  • middle author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • q-bio.BM1
same name
  • Fang Wu — 13 papers, h 16
  • Fang Wu — 13 papers, h 4
  • Fang Wu — 11 papers, h 6
  • Fang Wu — 8 papers, h 4
  • Fang Wu — 6 papers, h 4
  • Fang Wu — 6 papers, h 3

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 citedA Hierarchical Training Paradigm for Antibody Structure-sequence Co-design

3 citations · 3 across the 2 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modeling

Fang Wu, Stan Z. Li

Protein-protein interaction (PPI) represents a central challenge within the biology field, and accurately predicting the consequences of mutations in this context is crucial for dr…

cs.LG2025

Life-Code: Central Dogma Modeling with Multi-Omics Sequence Unification

Zicheng Liu, Siyuan Li, Zhiyuan Chen +6

The interactions between DNA, RNA, and proteins are fundamental to biological processes, as illustrated by the central dogma of molecular biology. Although modern biological pre-tr…

q-bio.BM2023★ 3 cited

A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design

Fang Wu, Stan Z. Li

Therapeutic antibodies are an essential and rapidly expanding drug modality. The binding specificity between antibodies and antigens is decided by complementarity-determining regio…

cs.LG2023

SemiReward: A General Reward Model for Semi-supervised Learning

Siyuan Li, Weiyang Jin, Zedong Wang +4

Semi-supervised learning (SSL) has witnessed great progress with various improvements in the self-training framework with pseudo labeling. The main challenge is how to distinguish…

◍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.