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Qiankun Li

36 papers hereh-index 9517 citations64 works total

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

author position
  • first author1
  • middle author25
  • last author5

Across the 31 of 36 papers where every author was matched, so the position is known.

fields
  • cs.CV18
  • cs.AI6
  • cs.LG4
  • cs.CL3
  • cs.CR2
  • cond-mat.str-el1
same name
  • Qiankun Li — 4 papers, h 12
  • Qiankun Li — 3 papers, h 5
  • Qiankun Li — 2 papers, h 1
  • Qiankun Li — 1 paper, h 5

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
20222026
most citedNeural Network Optimization Reimagined: Decoupled Techniques for Scratch and Fine-Tuning

9 citations · 12 across the 33 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

SaFeR-Steer: Evolving Multi-Turn MLLMs via Synthetic Bootstrapping and Feedback Dynamics

Haolong Hu, Hanyu Li, Tiancheng He +6

MLLMs are increasingly deployed in multi-turn settings, where attackers can escalate unsafe intent through the evolving visual-text history and exploit long-context safety decay. Y…

cs.LG2026

SaFeR-ToolKit: Structured Reasoning via Virtual Tool Calling for Multimodal Safety

Zixuan Xu, Tiancheng He, Huahui Yi +7

Vision-language models remain susceptible to multimodal jailbreaks and over-refusal because safety hinges on both visual evidence and user intent, while many alignment pipelines su…

cs.LG2026

Mem-T: Densifying Rewards for Long-Horizon Memory Agents

Yanwei Yue, Boci Peng, Xuanbo Fan +3

Memory agents, which depart from predefined memory-processing pipelines by endogenously managing the processing, storage, and retrieval of memories, have garnered increasing attent…

cs.LG2025

SaFeR-VLM: Toward Safety-aware Fine-grained Reasoning in Multimodal Models

Huahui Yi, Kun Wang, Qiankun Li +7

Multimodal Large Reasoning Models (MLRMs) demonstrate impressive cross-modal reasoning but often amplify safety risks under adversarial or unsafe prompts, a phenomenon we call the…

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