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Yoon Kim

11 papers hereh-index 7364 citations11 works total

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

author position
  • middle author11

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.LG1
same name
  • Yoon Kim — 23 papers, h 20
  • Yoon Kim — 14 papers, h 40
  • Yoon Kim — 11 papers, h 11
  • Yoon Kim — 8 papers, h 3
  • Yoon Kim — 8 papers, h 3
  • Yoon Kim — 6 papers, 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
20242026
most citedBayesian Teaching Enables Probabilistic Reasoning in Large Language Models

7 citations · 13 across the 10 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CL2025

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

Rulin Shao, Akari Asai, Shannon Zejiang Shen +18

Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are trained on easily verifiable short-form…

cs.LG2025

Learning to Interpret Weight Differences in Language Models

Avichal Goel, Yoon Kim, Nir Shavit +1

Finetuning (pretrained) language models is a standard approach for updating their internal parametric knowledge and specializing them to new tasks and domains. However, the corresp…

cs.CL2025

On the Same Wavelength? Evaluating Pragmatic Reasoning in Language Models across Broad Concepts

Linlu Qiu, Cedegao E. Zhang, Joshua B. Tenenbaum +2

Language use is shaped by pragmatics -- i.e., reasoning about communicative goals and norms in context. As language models (LMs) are increasingly used as conversational agents, it…

cs.CL2025★ 7 cited

Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models

Linlu Qiu, Fei Sha, Kelsey Allen +3

Large language models (LLMs) are increasingly used as agents that interact with users and with the world. To do so successfully, LLMs must construct representations of the world an…

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