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researcher

Xingjun Ma

16 papers hereh-index 435 citations17 works total

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

author position
  • middle author12
  • last author2

Across the 14 of 16 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.CL4
  • cs.CR4
  • cs.LG2
  • cs.CV1
  • cs.SI1
same name
  • Xingjun Ma — 47 papers, h 15
  • Xingjun Ma — 32 papers, h 28
  • Xingjun Ma — 22 papers, h 6
  • Xingjun Ma — 19 papers, h 4
  • Xingjun Ma — 8 papers, h 15
  • Xingjun Ma — 5 papers

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 citedOn the Adversarial Transferability of Generalized "Skip Connections"

1 citations · 1 across the 16 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Sci-MMR: Benchmarking Multi-Step Evidence-Grounded Scientific Reasoning in Multimodal Agents

Jiaqiang Li, Yajie Yang, Zhiheng Xi +15

Autonomous research agents are increasingly expected to search the literature, analyze experimental evidence, and generate scientific hypotheses. These capabilities require multi-s…

cs.AI2026

Safety Testing LLM Agents at Scale: From Risk Discovery to Evidence-Grounded Verification

Yunhao Feng, Ruixiao Lin, Ming Wen +12

LLM agents increasingly perform autonomous actions through external tools, leading to complex and evolving safety risks. However, existing safety testing targets expert-designed sa…

cs.AI2026

Mirror: A Multi-Agent System for AI-Assisted Ethics Review

Yifan Ding, Yuhui Shi, Zhiyan Li +10

Ethics review is a foundational mechanism of modern research governance, yet contemporary systems face increasing strain as ethical risks arise as structural consequences of large-…

cs.AI2025

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models

Yixu Wang, Xin Wang, Yang Yao +5

The rapid integration of Large Language Models (LLMs) into high-stakes domains necessitates reliable safety and compliance evaluation. However, existing static benchmarks are ill-e…

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