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Jianfeng Gao

9 papers hereh-index 582 citations15 works total

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

author position
  • middle author3
  • last author5

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.AI3
  • cs.LG2
same name
  • Jianfeng Gao — 153 papers, h 98
  • Jianfeng Gao — 102 papers, h 60
  • Jianfeng Gao — 25 papers, h 10
  • Jianfeng Gao — 20 papers, h 13
  • Jianfeng Gao — 14 papers, h 17
  • Jianfeng Gao — 12 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 citedMultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety

1 citations · 2 across the 8 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026★ 1 cited

MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety

Jialin Song, Xiaodong Liu, Weiwei Yang +4

We present MultiBreak, a scalable and diverse multi-turn jailbreak benchmark to evaluate large language model (LLM) safety. Multi-turn jailbreaks mimic natural conversational setti…

cs.CL2026

SEMA: Simple yet Effective Learning for Multi-Turn Jailbreak Attacks

Mingqian Feng, Xiaodong Liu, Weiwei Yang +4

Multi-turn jailbreaks capture the real threat model for safety-aligned chatbots, where single-turn attacks are merely a special case. Yet existing approaches break under exploratio…

cs.CL2025

SAS: Simulated Attention Score

Chuanyang Zheng, Jiankai Sun, Yihang Gao +12

The attention mechanism is a core component of the Transformer architecture. Various methods have been developed to compute attention scores, including multi-head attention (MHA),…

cs.CL2024

StreamAdapter: Efficient Test Time Adaptation from Contextual Streams

Dilxat Muhtar, Yelong Shen, Yaming Yang +11

In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks directly from the given demonstrations without requiring gradient updates. While recent advances…

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