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Junfeng Fang

40 papers hereh-index 14689 citations47 works total

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

author position
  • first author4
  • middle author31
  • last author1

Across the 36 of 40 papers where every author was matched, so the position is known.

fields
  • cs.LG16
  • cs.CL13
  • cs.CV4
  • cs.AI3
  • cs.IR2
  • cs.CR1
same name
  • Junfeng Fang — 13 papers, h 15
  • Junfeng Fang — 12 papers, h 3
  • Junfeng Fang — 8 papers, h 6
  • Junfeng Fang — 7 papers, h 2
  • Junfeng Fang — 2 papers, h 1
  • Junfeng Fang — 1 paper, 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
20242026
most citedAlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint

1 citations · 1 across the 24 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization

Jinghan Li, Junfeng Fang, Jinda Lu +5

Reinforcement Learning with Verifiable Rewards (RLVR) and Group Relative Policy Optimization (GRPO) have significantly advanced the reasoning capabilities of large language models.…

cs.CV2026

Active Zero: Self-Evolving Vision-Language Models through Active Environment Exploration

Jinghan He, Junfeng Fang, Feng Xiong +5

Self-play has enabled large language models to autonomously improve through self-generated challenges. However, existing self-play methods for vision-language models rely on passiv…

cs.CV2025

ACE: Concept Editing in Diffusion Models without Performance Degradation

Ruipeng Wang, Junfeng Fang, Jiaqi Li +4

Diffusion-based text-to-image models have demonstrated remarkable capabilities in generating realistic images, but they raise societal and ethical concerns, such as the creation of…

cs.CV2025

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs

Jinda Lu, Junkang Wu, Jinghan Li +6

Direct Preference Optimization (DPO) has shown effectiveness in aligning multi-modal large language models (MLLM) with human preferences. However, existing methods exhibit an imbal…

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