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Yongjin Yang

7 papers hereh-index 385 citations7 works total

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

author position
  • first author2
  • middle author5

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.AI3
same name
  • Yongjin Yang — 10 papers, h 5
  • Yongjin Yang — 4 papers, h 3
  • Yongjin Yang — 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

most citedCode-Switching Red-Teaming: LLM Evaluation for Safety and Multilingual Understanding

1 citations · 1 across the 6 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

IdeaScientist: Orchestrating Agents for Grounded Scientific Ideation

Jiarui Liu, Renjie Tao, Yiwei Liao +15

Despite rapid progress in automating scientific research, generating promising and well grounded research solutions remains a central challenge. We isolate research ideation as a s…

cs.CL2026

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning

Yinghui He, Ling Yang, Jiarui Liu +6

Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivation, then using the result t…

cs.CL2026

MixSD: Mixed Contextual Self-Distillation for Knowledge Injection

Jiarui Liu, Lechen Zhang, Yongjin Yang +5

Supervised fine-tuning (SFT) is widely used to inject new knowledge into language models, but it often degrades pretrained capabilities such as reasoning and general-domain perform…

cs.CL2026

Self-Distillation Zero: Self-Revision Turns Binary Rewards into Dense Supervision

Yinghui He, Simran Kaur, Adithya Bhaskar +7

Current post-training methods in verifiable settings fall into two categories. Reinforcement learning (RLVR) relies on binary rewards, which are broadly applicable and powerful, bu…

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