◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Kun Wang

15 papers hereh-index 5112 citations18 works total

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

author position
  • first author1
  • middle author11
  • last author1

Across the 13 of 15 papers where every author was matched, so the position is known.

fields
  • cs.AI5
  • cs.CL5
  • cs.LG3
  • cs.IR1
  • cs.SD1
same name
  • Kun Wang — 21 papers, h 9
  • Kun Wang — 19 papers, h 3
  • Kun Wang — 18 papers, h 11
  • Kun Wang — 17 papers, h 7
  • Kun Wang — 15 papers, h 5
  • Kun Wang — 14 papers, h 12

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
20242026
most citedSkillNet: Create, Evaluate, and Connect AI Skills

1 citations · 1 across the 14 of their papers we have counts for

collaborators
Showing 2026 · cs.AIShow all

4 papers · 2 filters

cs.AI2026

Distance Is Not Enough: Forget-Retain Alignment Gap Predicts LLM Relearning Robustness

Yi Chen, Hanna Hsieh, Shuhong Liu +4

Machine unlearning aims to make a model forget specific data, yet unlearned LLMs often fail to stay unlearned: brief fine-tuning can revive removed knowledge. Existing robustness p…

cs.AI2026

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion

ShiYing Huang, Liang Lin, Yuer Li +6

In the realm of multi-objective alignment for large language models, balancing disparate human preferences often manifests as a zero-sum conflict. Specifically, the intrinsic tensi…

cs.AI2026

MineEvolve: Self-Evolution with Accumulated Knowledge for Long-Horizon Embodied Minecraft Agents

Zhengwei Xie, Zhisheng Chen, Ziyan Weng +7

Long-horizon embodied intelligence requires agents to improve through interaction, not merely to execute plans generated from static goals. A central challenge is therefore to tran…

cs.AI2026★ 1 cited

SkillNet: Create, Evaluate, and Connect AI Skills

Yuan Liang, Ruobin Zhong, Haoming Xu +47

Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumulation and transfer of skills. Wi…

◍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.